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Understanding landscape barriers to connectivity is essential for studying wildlife population dynamics and developing conservation strategies that promote genetic exchange. Rivers can fragment landscapes and thereby influence genetic metapopulation structure by restricting individual movement and gene flow, yet their impact on brown bear ( Ursus arctos ) dispersal remains poorly understood. Using a large dataset (N = 519) of SNP-genotypes (96 loci) from fecal samples, we investigated the effects of rivers on sex-specific movement patterns, primarily dispersal and genetic structure in brown bears in northern Sweden. We found that males dispersed over twice as far as females (mean 56.4 km vs. 22.8 km) and crossed rivers significantly more often (42% of male vs. 11% of female dispersals; χ 2  = 49.33, p  < 0.001). Simulated female dispersals in random directions showed higher river crossings (17.7%, t = 90.47, p  < 0.001), suggesting philopatry alone cannot explain the low observed crossing rate. Rivers thus acted as semipermeable barriers for females, with genetic structure analysis (DAPC, spatial PCA) showing weak structuring effects for females, but none for males. Our study underscores the need to identify specific crossing sites, evaluate additive effects of other barriers (e.g., roads), and expand research across Sweden to guide connectivity-focused conservation.

The concept of ecotypes is complex, partly because of its interdisciplinary nature, but the idea is intrinsically valuable for evolutionary biology and applied conservation. The complex nature of ecotypes has spurred some confusion and inconsistencies in the literature, thereby limiting broader theoretical development and practical application. We provide suggestions for how incorporating genetic analyses can ease confusion and help define ecotypes. We approach this by systematically reviewing 112 publications across taxa that simultaneously mention the terms ecotype, conservation and management, to examine the current use of the term in the context of conservation and management. We found that most ecotype studies involve fish, mammals and plants with a focus on habitat use, which at 60% was the most common criterion used for categorization of ecotypes. Only 53% of the studies incorporated genetic analyses, and major discrepancies in available genomic resources among taxa could have contributed to confusion about the role of genetic structure in delineating ecotypes. Our results show that the rapid advances in genetic methods, also for nonmodel organisms, can help clarify the spatiotemporal distribution of adaptive and neutral genetic variation and their relevance to ecotype designations. Genetic analyses can offer empirical support for the ecotype concept and provide a timely measure of evolutionary potential, especially in changing environmental conditions. Genetic variation that is often difficult to detect, including polygenic traits influenced by small contributions from several genes, can be vital for adaptation to rapidly changing environments. Emerging ecotypes may signal speciation in progress, and findings from genome‐enabled organisms can help clarify important selective factors driving ecotype development and persistence, and thereby improve preservation of interspecific genetic diversity. Incorporation of genetic analyses in ecotype studies will help connect evolutionary biology and applied conservation, including that of problematic groups such as natural hybrid organisms and urban or anthropogenic ecotypes.

Quantifying dispersal within wild populations is an important but challenging task. Here we present a method to estimate contemporary, individual‐based dispersal distance from noninvasively collected samples using a specialized panel of 96 SNPs (single nucleotide polymorphisms). One main issue in conducting dispersal studies is the requirement for a high sampling resolution at a geographic scale appropriate for capturing the majority of dispersal events. In this study, fecal samples of brown bear (Ursus arctos) were collected by volunteer citizens, resulting in a high sampling resolution spanning over 45,000 km2 in Gävleborg and Dalarna counties in Sweden. SNP genotypes were obtained for unique individuals sampled (n = 433) and subsequently used to reconstruct pedigrees. A Mantel test for isolation by distance suggests that the sampling scale was appropriate for females but not for males, which are known to disperse long distances. Euclidean distance was estimated between mother and offspring pairs identified through the reconstructed pedigrees. The mean dispersal distance was 12.9 km (SE 3.2) and 33.8 km (SE 6.8) for females and males, respectively. These results were significantly different (Wilcoxon's rank‐sum test: P‐value = 0.02) and are in agreement with the previously identified pattern of male‐biased dispersal. Our results illustrate the potential of using a combination of noninvasively collected samples at high resolution and specialized SNPs for pedigree‐based dispersal models. Quantifying dispersal is an important but difficult task. Here we estimate dispersal distance for the Swedish brown bear using a highly‐informative SNP‐panel and pedigree‐reconstruction from non‐invasively collected samples by citizens. Our results are comparable to other methods and thereby illustrate the potential for other species requiring non‐invasive sampling.

Harmonising methodology between countries is crucial in transborder population monitoring. However, immediate application of alleged, established DNA-based methods across the extended area can entail drawbacks and may lead to biases. Therefore, genetic methods need to be tested across the whole area before being deployed. Around 4,500 brown bears (Ursus arctos) live in Norway, Sweden, and Finland and they are divided into the western (Scandinavian) and eastern (Karelian) population. Both populations have recovered and are connected via asymmetric migration. DNA-based population monitoring in Norway and Sweden uses the same set of genetic markers. With Finland aiming to implement monitoring, we tested the available SNP-panel developed to assess brown bears in Norway and Sweden, on tissue samples from a representative set of 93 legally harvested individuals from Finland. The aim was to test for ascertainment bias and evaluate its suitability for DNA-based transnational-monitoring covering all three countries. We compared results to the performance of microsatellite genotypes of the same individuals in Finland and against SNP-genotypes from individuals sampled in Sweden (N = 95) and Norway (N = 27). In Finland, a higher resolution for individual identification was obtained for SNPs (PI = 1.18E-27) compared to microsatellites (PI = 4.2E-11). Compared to Norway and Sweden, probability of identity of the SNP-panel was slightly higher and expected heterozygosity lower in Finland indicating ascertainment bias. Yet, our evaluation show that the available SNP-panel outperforms the microsatellite panel currently applied in Norway and Sweden. The SNP-panel represents a powerful tool that could aid improving transnational DNA-based monitoring of brown bears across these three countries.

Determination of parentage provides valuable information for the conservation of wild populations, for instance, by allowing the monitoring of breeding success and inbreeding. Between 1999 and 2002, nine brown bears ( Ursus arctos ) were translocated to augment the remnant population of a few surviving individuals in the Italian Alps, but only part of them reproduced, with a higher inbreeding risk occurrence in the long-time. Currently, in the Alpine population, parentage tests are assessed through the analysis of 15 microsatellite loci (STRs), but the reduction of genetic variability in future generations will need the use of additional informative markers. Single nucleotide polymorphisms (SNPs) have been proven to be useful and reliable in individual identification and family reconstruction; moreover, they can perform well on low-quality samples. In this study, we analysed 51 SNPs to generate a SNP multilocus genotype dataset of 54 Alpine brown bears ( Ursus arctos ) and compared its performance in parentage analysis with the validated STR dataset. We found that SNPs alone are not sufficient to determine parentage relationships, but the combination of SNPs and STRs provided unambiguous parentage assignments. The combined panel also performed better than STRs when true parents were not present in the dataset and, consequently, showed higher values of assignment probabilities.

Information about relatedness between individuals in wild populations is advantageous when studying evolutionary, behavioural and ecological processes. Genomic data can be used to determine relatedness between individuals either when no prior knowledge exists or to confirm suspected relatedness. Here we present a set of 96 SNPs suitable for inferring relatedness for brown bears (Ursus arctos) within Scandinavia. We sequenced reduced representation libraries from nine individuals throughout the geographic range. With consensus reads containing putative SNPs, we applied strict filtering criteria with the aim of finding only high-quality, highly-informative SNPs. We tested 150 putative SNPs of which 96% were validated on a panel of 68 individuals. Ninety-six of the validated SNPs with the highest minor allele frequency were selected. The final SNP panel includes four mitochondrial markers, two monomorphic Y-chromosome sex-determination markers, three X-chromosome SNPs and 87 autosomal SNPs. From our validation sample panel, we identified two previously known parent-offspring dyads with reasonable accuracy. This panel of SNPs is a promising tool for inferring relatedness in the brown bear population in Scandinavia.

Brown bears in Italy persist in two isolated populations, one in the Alpine and the other in the Apennine mountain range. Both are threatened and elusive. Non-invasive genetics provides a good way to monitor the populations. Microsatellites (STRs) have been the marker of choice for non-invasive genetic monitoring, but due to non-invasive bad quality samples, these analyses were plagued by low amplification rates and genotyping errors. Moreover, to compare microsatellite genotypes, allele calibration is needed between laboratories, leading to difficulties in individual identification. In contrast, SNP genotyping is directly comparable between laboratories, and more sensitive and accurate. Here we test a 96-marker SNP chip developed for the Scandinavian brown bear population on the Italian populations. A subset of these SNPs was found informative and could reliable confirm species, sex and, only in the Alpine population, distinguish individuals. A total of 51 informative SNPs provided better resolution power than 15 STRs, used in the routine monitoring of the Alpine population in Italy. In contrast, only 15 SNPs were found to be informative for the Apennine population, which did not have enough resolution to discriminate individuals and were less informative than 11 STRs. While highly useful in the Alpine population, additional SNP markers must be included to reach the same level of resolution in the Apennine population.

Biodiversity loss threatens ecosystems and human well-being, making accurate, large-scale monitoring crucial. Environmental DNA (eDNA) has enabled species detection from substrates such as water, without the need for direct observation. Lately, airborne eDNA has been showing promise for tracking organisms from insects to mammals in terrestrial ecosystems. Conventional biodiversity assessments are often labor-intensive and limited in scope, leaving gaps in our understanding of ecosystem response to environmental change. Here, we demonstrate that airborne eDNA can detect organisms across the tree of life, quantify changes in abundance congruent with traditional monitoring, and reveal land-use induced regional decline of diversity in a northern boreal ecosystem over more than three decades. By analyzing 34 years of archived aerosol filters, we reconstruct weekly temporal relative abundance data for more than 2700 genera using non-targeted methods. This study provides unified, ecosystem-scale biodiversity surveillance spanning multiple decades, with data collected at weekly intervals on both the individual species and community level. Previously, large scale analyses of ecosystem changes, targeting all types of organisms, has been prohibitively expensive and difficult to attempt. Here, we present a way of holistically doing this type of analysis in a single framework. Quantifying ecosystem dynamics is critical in the face of rapid environmental change. This study uses airborne eDNA to quantify changes in organism abundances across the tree of life and reveal a regional decline in biodiversity over three decades.

Context Methods for detecting contemporary, fine-scale population genetic structure in continuous populations are scarce. Yet such methods are vital for ecological and conservation studies, particularly under a changing landscape. Objectives Here we present a novel, spatially explicit method that we call landscape relatedness (LandRel). With this method, we aim to detect contemporary, fine-scale population structure that is sensitive to spatial and temporal changes in the landscape. Methods We interpolate spatially determined relatedness values based on SNP genotypes across the landscape. Interpolations are calculated using the Bayesian inference approach integrated nested Laplace approximation. We empirically tested this method on a continuous population of brown bears ( Ursus arctos ) spanning two counties in Sweden. Results Two areas were identified as differentiated from the remaining population. Further analysis suggests that inbreeding has occurred in at least one of these areas. Conclusions LandRel enabled us to identify previously unknown fine-scale structuring in the population. These results will help direct future research efforts, conservation action and aid in the management of the Scandinavian brown bear population. LandRel thus offers an approach for detecting subtle population structure with a focus on contemporary, fine-scale analysis of continuous populations.

Parrots (Psittaciformes) are among the most endangered groups of birds today and remain threatened by habitat loss and exploitation for the live bird trade. Under such conditions, reliable and non-invasive monitoring techniques are crucial for successful conservation measures. In this study, we developed a panel of 86 high quality SNPs for genotyping endangered sun parakeets ( Aratinga solstitialis ) in Guyana, which form one of the last known breeding populations of this South American species in the wild. Genotyping was tested on different types of samples (blood, feathers, feces, beak and cloacal swabs). While blood performed best, feathers and feces also yielded reliable results and could thus be used as non-invasive sources of DNA for future population monitoring. Discriminant Analysis of Principal Components (DAPC) on genotypes revealed that Guyanese sun parakeets clustered separately from other psittacine species as well as conspecifics from a captive population. A priori known first-order kinships were also adequately detected by the SNP panel. Using a series of experimental contaminations, we found that contamination from other psittacine species and slight contamination (~ 10%) from conspecifics did not prevent successful genotyping and recognition of individuals. We show that instances of higher conspecific contamination (~ 50%) can be detected through an increased level of heterozygosity that falls outside the distribution of uncontaminated samples.