The question of subspecies identity matters far more than a taxonomic technicality. Globally, the brown bear is listed as Least Concern by the IUCN, but that sweeping label conceals sharp regional declines. In Nepal, the species is classified as Critically Endangered, with fewer than 20 mature individuals estimated nationwide and a distribution restricted to the northern high Himalayas. The species enjoys full legal protection under Nepal’s National Parks and Wildlife Conservation Act of 1973, yet conservation planning has been hampered by a fundamental problem: nobody knew for certain which bear they were protecting. Historical records relied on indirect signs, local reports, and photographs, none of which could reliably distinguish the Tibetan brown bear from its Himalayan relative, whose range is centered on northern Pakistan and northwestern India.

Previous mitochondrial DNA studies had shown that the two subspecies represent genetically distinct evolutionary lineages despite their geographic proximity. The Tibetan brown bear occupies the Tibetan Plateau and adjoining high-altitude regions, while the Himalayan brown bear is largely confined to the northwestern Himalaya. But no genetic study of brown bears had ever been conducted within Nepal itself. The new research, led by Rishi Baral of Hokkaido University and colleagues, set out to close that gap by sampling two key landscapes: Mustang District within the Annapurna Conservation Area and Dolpa District within Shey-Phoksundo National Park, both characterized by cold arid climates, rugged terrain, and alpine steppe vegetation.

Between 2022 and 2024, field teams working with experienced local personnel collected ten non-invasive samples putatively attributed to brown bears, seven fecal samples and three hair samples, located using associated field signs such as tracks, digging marks, and feeding sites. The researchers swabbed the outer mucosal layer of feces with sterile swabs preserved in buffer, collected hair with sterilized forceps, and geo-referenced every sample with handheld GPS units before storage at minus 20 degrees Celsius. In the laboratory, DNA was extracted under sterile conditions with negative controls to monitor contamination, and a short fragment of the mitochondrial control region, the D-loop, was amplified using bear-specific primers designed for subspecies discrimination.

The genetic results were strikingly clear. Seven of the ten samples yielded successful mitochondrial sequences, and every one of them carried the same haplotype, one that phylogenetic analysis placed firmly within the Tibetan brown bear lineage. The Nepalese sequences formed a well-supported clade with reference samples from the Tibetan Plateau, while the Himalayan brown bear emerged as a distinct sister lineage, clearly separate. Bootstrap support values for the major nodes exceeded 70 percent, and the sloth bear served as a divergent outgroup. Haplotype diversity and nucleotide diversity were both zero, meaning no mitochondrial variation was detectable among the samples analyzed, a pattern consistent with historical bottlenecks, long-term isolation, and restricted female dispersal reported for Tibetan brown bears across their core range.

Microsatellite genotyping, though successful in only 40 percent of samples, a common limitation with degraded non-invasive material, identified two unique individuals, both male. One was detected in Upper Mustang from a single hair sample, and the other from three fecal samples collected in Dolpa. The male-only detection pattern fits a well-documented trend in bear genetics: males disperse farther and hold larger home ranges, so they are more frequently encountered in surveys, while females tend to remain near their birthplaces. That sex bias raises the possibility that female-mediated gene flow into Nepal is particularly limited, potentially deepening the genetic isolation of any resident bears or linking them only through seasonal movement across the Tibetan border.

The camera-trap data provided independent ecological corroboration. As part of a broader mammalian community survey, the team deployed 96 motion-triggered infrared camera stations, 64 in Mustang and 32 in Dolpa, arranged on a systematic 4-by-4-kilometer grid across elevations of roughly 3,500 to 5,600 meters, with stations separated by at least 2 kilometers and no bait or scent lures used. Over 9,336 camera-trap nights of effort, the traps recorded four independent brown bear capture events at three stations in Upper Mustang between April 2023 and June 2024, at elevations from 3,834 to 4,816 meters across alpine steppe, shrubland, and grassland. One bear was photographed twice in a single day at Lomanthang, moving upslope at dawn and downslope in the evening, apparently after concealing itself from five feral dogs detected nearby. Another individual spent the night of June 5, 2023 playing and jumping in front of a camera at Damodar Kunda. In Dolpa, cameras set for long-term snow leopard monitoring captured four additional brown bear detections in 2023 and 2024, including one animal that paused to inspect the lens at nearly 5,000 meters.

Independent experts from the IUCN Species Survival Commission’s Bear Specialist Group reviewed the photographs and consistently judged the recorded animals consistent with the Tibetan brown bear, citing pale to dark brown pelage, prominent shoulder humps, and concave facial profiles. The study also compiled a verified photograph of a live bear taken by a local horse owner above Samdo village in the Manaslu Conservation Area, showing an individual feeding on a carcass, evidence of either scavenging or predation. Synthesizing these records with published reports spanning 2008 to 2025, the authors mapped confirmed brown bear occurrence across several Trans-Himalayan landscapes, including Humla, Dolpa, Mustang, Manaslu, and the Kanchenjunga Conservation Area, all along the southern periphery of the species’ global range.

The authors are careful to note the limits of their data. With only two genetically confirmed individuals and no detectable mitochondrial variation, the study cannot yet demonstrate a resident breeding population in Nepal. Some detected animals may be dispersing or transient males from larger populations on the Tibetan Plateau. Whether Nepal supports permanent residents, seasonal migrants, or a movement corridor connecting Himalayan and Plateau populations remains an open question that will require expanded non-invasive sampling targeting females, nuclear genomic markers to assess connectivity and effective population size, and long-term monitoring across the fragmented alpine habitat.

Still, the repeated detections across multiple years and locations suggest that Nepal’s Trans-Himalayan landscapes are regularly used by brown bears rather than visited by accident. For a nationally Critically Endangered carnivore at the edge of its range, that distinction carries real weight. Peripheral populations often show reduced genetic diversity and heightened vulnerability to environmental change, infrastructure development, livestock grazing, and human-bear conflict, but they can also serve as stepping stones or refugia under future climate scenarios. The researchers argue that maintaining landscape connectivity across Trans-Himalayan corridors and mitigating conflict in pastoral communities should be immediate priorities, alongside transboundary collaboration with counterparts in China. The study establishes the first molecular baseline for Tibetan brown bears in Nepal and demonstrates how genetics, camera trapping, and local ecological knowledge can be woven together to illuminate the lives of species that dwell where few observers can follow.

Subject of Research: Genetic and camera-trap confirmation of the Tibetan brown bear (Ursus arctos pruinosus) in central Nepal

Article Title: Confirmation of the Tibetan Brown Bear (Ursus arctos pruinosus) in Central Nepal Based on Genetic and Camera‐Trap Evidence

Article References: Baral, R., Gurung, R. B., Sapkota, A., Subedi, N., Giordano, A. J., Paudel, R. P., Kadariya, R., Khanal, G., Kodzue, K., Tsubota, T., & Shimozuru, M. (2026). Confirmation of the Tibetan Brown Bear ( Ursus arctos pruinosus ) in Central Nepal Based on Genetic and Camera‐Trap Evidence. Ecology and Evolution, 16(10), Article e74400. https://doi.org/10.1002/ece3.74400

Image Credits: AI Generated

DOI: 10.1002/ece3.74400

Keywords: Tibetan brown bear, Ursus arctos pruinosus, Nepal, mitochondrial DNA, camera trapping, non-invasive genetics, Trans-Himalaya, conservation, phylogeography, Annapurna Conservation Area, critically endangered, wildlife monitoring

The research team, working with the conservation organisation Rewilding Apennines as part of the LIFE ESC360 project, assembled 69 spatially explicit wildcat occurrence records collected between 2009 and 2023. The records spanned the full length of the country, from Friuli-Venezia Giulia in the northeast to the slopes of Mount Etna in Sicily, and drew on three independent datasets: the national ‘Progetto Gatto Selvatico’ archive, new camera-trapping surveys in Abruzzo, and previously published records from Etna Regional Park. To ensure data reliability, records from the national project were classified under the SCALP scheme, a verification framework originally developed for large-carnivore monitoring, yielding 11 genetically or morphologically confirmed records and 24 supported by unambiguous camera-trap photographs of wild-type individuals.

With those occurrences in hand, the team built a species distribution model using MaxEnt 3.4.3, a maximum-entropy algorithm designed for presence-only data. Environmental predictors were deliberately kept parsimonious to avoid overfitting: eight land-cover variables derived from the CORINE Land Cover 2018 dataset, aggregated to reflect habitat types relevant to wildcats, plus average elevation from the SRTM digital elevation model. Because camera traps and carcass recoveries are not distributed evenly across the landscape, the researchers generated a kernel density surface of sampling effort and used it to bias the selection of 10,000 background points, so that the model would not simply relearn where humans had looked. Model tuning via the ENMeval package selected hinge features and a regularisation multiplier of 3, and the final model was validated against a distribution of 100 null-model iterations.

The results were strikingly clear. The model achieved an AUC of 0.81, well above the null-model median of 0.50, and two variables dominated the prediction: forest and grassland cover contributed 62.5 percent of the model’s explanatory power, with a permutation importance of 78.6 percent, while average elevation contributed a further 36.1 percent. The response curves showed that the probability of wildcat occurrence rose sharply with increasing forest and grassland cover, levelling off at roughly 70 to 75 percent cover, and climbed with elevation up to about 1,000 metres above sea level before plateauing. Urban fabric, roads, agriculture, and water bodies contributed essentially nothing to the model. Mapped across Italy, the highest suitability values traced the spine of the Apennine chain and the Alpine region, with lower but non-negligible suitability in lowland and coastal zones.

To test whether these predictions held up on the ground, the researchers collected 23 new wildcat occurrences in the Central–Southern Apennines, none of which had been used to calibrate the model. Sixteen tissue samples came from carcasses, mostly roadkill and a few accidental hunting bycatch, recovered by rangers in the Abruzzo, Lazio and Molise National Park and the Regional Natural Park of the Simbruini Mountains. Seven further occurrences came from non-invasive monitoring combining camera traps with hair traps, wooden poles wrapped in Velcro and laced with valerian tincture, deployed in the Monte Genzana–Alto Gizio Regional Nature Reserve and the Sirente–Velino Regional Natural Park. When the sampling locations were overlaid on the prediction map, most fell within areas of relatively high predicted occurrence probability, an encouraging sign that the model captures real ecological signal rather than statistical artefact.

The genetic analysis, however, delivered the study’s most provocative twist. The team sequenced an 835-base-pair fragment of the mitochondrial MT-ND5 gene, a marker favoured in felid phylogenetics because it carries low homoplasy and is free of nuclear mitochondrial pseudogenes, trimming the sequences to 669 base pairs for comparison with a European reference dataset. Among 21 successfully sequenced individuals, all of which had been phenotypically classified as wildcats based on diagnostic pelage traits, the researchers found just four haplotypes grouped into three haplogroups. Only two individuals, roughly 10 percent, carried a ‘w’ haplotype reported exclusively in European wildcats. The remaining 90 percent carried maternal lineages shared with domestic cats: the dw1 haplotype accounted for 71.4 percent of samples and dw4 for 14.3 percent, while a single individual carried the domestic-type d3 haplotype.

One finding in particular stands out. The w12 haplotype, detected in two Apennine individuals, had previously been recorded in only one animal across a broad European dataset: a wildcat from Spain assigned to Felis silvestris on the basis of nuclear markers, where it was interpreted as a private Iberian lineage potentially reflecting historical isolation south of the Pyrenees. Its appearance in central Italy extends the known geographic range of this rare maternal lineage well beyond Iberia and adds to the mitochondrial diversity documented for Italian wildcats. The authors are careful, however, to note that because mitochondrial DNA is maternally inherited and represents a single non-recombining locus, this detection should not by itself be read as evidence of a direct phylogeographic connection between Italian and Iberian populations.

What, then, do the domestic-type maternal lineages mean? The answer is more nuanced than a simple hybridisation alarm. Recent genome-wide work suggests that contemporary interbreeding between wildcats and domestic cats is limited despite centuries of sympatry across Europe, which makes historical introgression a plausible contributor to the mitochondrial patterns observed here. The study’s ND5 data alone cannot establish the timing or extent of admixture; distinguishing recent hybridisation from ancient gene flow would require nuclear or genome-wide markers. There are also caveats of scale: successful sequences came from only 21 samples, and because individual identity could not be genetically confirmed for all hair samples, the apparent dominance of the dw1 haplotype may be inflated, since three hair samples sharing it were collected at the same location within a short timeframe. The haplotype frequencies should therefore be treated as preliminary.

The mismatch between pelage-based identification and mitochondrial assignment also carries a methodological warning. Diagnostic coat characteristics, such as the thick ringed tail and distinctive dorsal stripe described in classic identification keys, remain a practical field tool, but phenotypic overlap between wildcats, domestic cats, and admixed individuals means some misclassification is inevitable. That uncertainty propagates into the occurrence records underlying the distribution model itself, and the authors recommend interpreting habitat suitability patterns with this in mind. Interestingly, statistical comparison of predicted occurrence probabilities across sample categories showed that phenotypically wild individuals without genetic data occupied significantly more suitable habitat than any genetic category, hinting that the most remote, least disturbed areas may host the least admixed animals.

For conservation planners, the practical message is concrete. The Apennine chain emerges as the critical connective infrastructure for Italian wildcats, and protecting forest and grassland across suitable elevational gradients should be the priority, alongside ecological corridors and buffer zones that maintain landscape connectivity. The authors also point to precautionary measures in areas of sympatry, including responsible pet ownership and monitoring of feral cat populations to reduce wildcat–domestic cat interactions. Set against global biodiversity targets such as protecting 30 percent of terrestrial areas by 2030, the study offers a template: combine habitat modelling, updated field occurrence data, and genetic monitoring, supported by citizen science, to build an evidence base strong enough to guide action. For a species so adept at vanishing into the Mediterranean maquis, that combination of eyes and molecules may be the only reliable way to keep track of Europe’s last truly wild cat.

Subject of Research: Conservation genetics and habitat suitability modelling of the European wildcat in Italy

Article Title: Checking Wilderness Through Conservation Genetics: The Case of the European Wildcat in the Central Apennines, Italy

Article References: Maini, M., Polce, C., Bernini, F., Longeri, M., Milanesi, R., Caniglia, R., Mattucci, F., Velli, E., & Gatti, R. C. (2026). Checking Wilderness Through Conservation Genetics: The Case of the European Wildcat in the Central Apennines, Italy. Ecology and Evolution, 16(9), Article e74418. https://doi.org/10.1002/ece3.74418

Image Credits: AI Generated

DOI: 10.1002/ece3.74418

Keywords: European wildcat, Felis silvestris, conservation genetics, species distribution model, MaxEnt, mitochondrial DNA, Apennines, Italy, hybridisation, habitat suitability, camera trapping, wildlife monitoring

The research team, led by Tamandra H. D’Ombrain of La Trobe University, focused on sambar deer, the most abundant introduced deer species in Victoria, where an estimated 123,061 animals roam public land. Sambar are elusive creatures, and managing them, alongside five other established deer species, has long been hampered by the difficulty of monitoring populations that are widely dispersed, wary of people and expensive to track. Traditional genetic studies have relied almost entirely on tissue samples from culling and recreational hunting, meaning data collection has been opportunistic and restricted to dead animals, precluding repeated sampling of living individuals for mark-recapture population estimates, movement tracking, or before-and-after comparisons of control programs.

To break that bottleneck, the team turned to Genotyping-in-Thousands by sequencing, or GT-seq, a method that uses custom amplicon sequencing of hundreds of targeted DNA loci via a single multiplexed PCR reaction. Unlike reduced-representation sequencing approaches such as DArTseq or RADseq, which can generate thousands of markers but demand high-quality DNA and substantial budgets, GT-seq is designed for exactly the kind of short, degraded, contaminated DNA that faecal samples contain. Species-specific primers and relatively short fragments make it well suited to non-invasive material, and it has already been applied successfully to coyote scats, polar bear faeces, tiger dung and even archival fish scales.

Building the panel required careful balancing. The researchers drew on existing DArTseq data from 739 tissue and blood samples of sambar, rusa and fallow deer across Australia, deliberately selecting markers that could be co-analysed with a decade of existing sambar genetic data. Simulations indicated that at least 200 highly variable SNPs would be needed for reliable individual identification in a species with low genetic diversity stemming from the small number of founding individuals. After iterative rounds of primer design, testing and optimisation, anchored to the closest available reference genome, the red deer mCerEla1.1 assembly, the final panel contained 371 autosomal SNP loci plus three newly designed sex markers, all amplified in a single PCR. Twenty-one loci were deliberately fixed between sambar and rusa, allowing hybridisation, a genuine management concern in southeastern Australia, to be detected.

The heart of the study, and its most striking contribution, was a degradation experiment. Colon sections containing faecal material were collected by Parks Victoria during control operations in northeast Victoria, giving the researchers paired tissue and dung from the same individuals and a uniform starting point. Pellets were distributed across three conditions: fully exposed outdoors, protected from rain and ultraviolet light beneath a 99 percent UV-blocking polycarbonate sheet, and kept indoors at room temperature. Samples were swabbed for DNA after zero, two, four, seven and fourteen days, during a period in October 2023 that included 35.6 millimetres of rainfall and typical spring temperatures. In total, 12.8 million paired-end reads were generated, with 56 percent landing squarely on target loci.

The results were unambiguous. Fresh faecal samples performed as well as, or better than, colon tissue, genotyping an average of 300 of 374 loci. Pellets kept indoors showed virtually no decline, and even fourteen days later the indoor samples still yielded more than 300 loci on average. Protected pellets likewise remained viable throughout the study, with no statistically significant loss of genotyping rate or increase in error. But fully exposed pellets told a different story. Their genotyping rate declined steeply over time, dropping to an average of just 76 loci by day fourteen, while their error rate climbed from 1.4 percent at day two to 13.1 percent at day fourteen. With rain striking on six days of the trial, the researchers concluded that rainfall, rather than sunlight, is the primary driver of DNA loss, consistent with earlier microsatellite work but contrasting with a handful of SNP-based studies conducted under more sheltered, simulated conditions.

The practical implications for field sampling are considerable. Pellets exposed to rain and UV remained usable for roughly four days on average, whereas sheltered samples survived well beyond two weeks. The team recommends sampling during dry spells, prioritising fresh-looking pellets or those protected by vegetation, and avoiding collection immediately after rain, when rehydrated pellets can appear deceptively fresh. Crucially, hard, dry pellets should not be discarded: desiccation itself preserves DNA, and a pellet that looks ancient may still genotype beautifully. The study also showed that visual appearance alone is an unreliable guide, reinforcing calls for research into whether pellet characteristics such as colour and texture can predict genotyping success.

Accuracy, not just yield, was the study’s second battleground. Without filtering, degraded samples produced genetic distances that could scramble individual identities, making different animals appear alike or the same animal appear different. But with a simple two-step filtering threshold, excluding samples with more than 50 percent missing data and then loci with more than 20 percent missing, the panel achieved 100 percent accurate individual assignment using a genetic distance cut-off of 0.1. The three new sex markers, designed from conserved regions between the X and Y chromosomes of deer and other even-toed ungulates, correctly assigned sex in every fresh, indoor and protected sample, with errors appearing only in heavily degraded exposed samples, and never in individuals whose genotyping rate exceeded 0.5.

Perhaps most importantly for managers, the panel proved compatible with the existing DArTseq datasets that underpin sambar monitoring. Discordance between faecal and tissue genotypes from the same individual was below one percent, comparable to the best published GT-seq faecal studies, and discordance with DArTseq data, though higher at around three percent, remained low enough for co-analysis. When the 200 most reliably genotyped SNPs were tested against a filtered dataset of 7,412 SNPs, both recovered the same three main population clusters across southeastern Australia, and pairs flagged as close relatives in the small dataset were almost always close in the large one. The authors caution that kinship resolution is coarser with 200 markers and that high background relatedness among sambar complicates precise relationship classification, but first-order kinship and broad population structure remain firmly within reach.

At an estimated AUD 36 per sample for consumables, with a plate of 96 samples processed from extraction to sequencing in one to two weeks, the panel offers a realistic route to large-scale, non-invasive genetic monitoring of living deer. That opens the door to genetic mark-recapture population estimates, evaluation of control programs, dispersal tracking and early detection of hybrids or new populations, all without ever handling an animal. The study is, to the authors’ knowledge, the first to quantify environmental degradation effects on GT-seq faecal genotyping, and its lessons, sample fresh, sample dry, filter stringently, extend far beyond deer, offering a blueprint for non-invasive genetic monitoring of both invasive and threatened species worldwide.

Subject of Research: Development of a GT-seq SNP amplicon panel for non-invasive genotyping of invasive sambar deer faecal pellets and the effects of environmental exposure on faecal DNA degradation and genotyping success.

Article Title: Development of a SNP Amplicon Panel for Invasive Deer Faecal Pellets and the Effects of Environmental Exposure on Genotyping Success

Article References: D'Ombrain, T. H., Harrisson, K. A., Pacioni, C., Hill, E., & Murphy, N. P. (2026). Development of a SNP Amplicon Panel for Invasive Deer Faecal Pellets and the Effects of Environmental Exposure on Genotyping Success. Ecology and Evolution, 16(9), Article e74388. https://doi.org/10.1002/ece3.74388

Image Credits: AI Generated

DOI: 10.1002/ece3.74388

Keywords: sambar deer, faecal DNA, GT-seq, SNP panel, non-invasive genetic sampling, DNA degradation, wildlife monitoring, invasive species, population genetics, genotyping error, individual identification, Australia