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We collected snow from polar bears and Eurasian lynx snow tracks in the wild and in captivity, and from a snow leopard in captivity. For all three species we retrieved reference material (hair, saliva, nasal mucus) as positive controls to refine methods and verify the accuracy of snow tracks for microsatellite genotyping. Hair samples were stored in dry envelopes at room temperature (RT), and saliva samples were dried and stored at RT. The field protocol for collecting eDNA from polar bear and snow leopard snow tracks was adapted from previous trials with Eurasian lynx and European otter (Lutra lutra) in Sweden in 2017 and 2018. It includes detailed field sampling, filtering, and fixation protocols ( Supplementary Material S1 ). Information recorded during sample collection included date, number of snow tracks (individual paw impressions), air temperature, geographical coordinates of sampling locations, collection vessels, type of filters, and volume of melted snow filtered ( Table S1 ). All samples were fixed in ethanol 200 proof Molecular Biology Grade (Thermo Fisher Scientific Inc., Waltham, MA, USA).

Wild polar bear snow tracks were collected in the vicinity of Utqiaġvik, Alaska, United States of America ( Figure 1 ) in January 2019 and May 2022. Field crews included staff from the North Slope Borough Department of Wildlife Management, Utqiaġvik, Alaska and individuals from the Inupiat community, who had extensive knowledge of the area, environment and working in extreme conditions. Snow tracks were detected visually from snow mobiles and collected when discovered. Tracks clearly created by more than one individual were not collected. Sampling of fresh snow tracks and corresponding hair samples as positive controls from captive polar bears took place in 2018 from Orsa predator park, Sweden and Rauna Zoo, Finland.

Wild Eurasian lynx snow tracks were collected from several locations across central and southern Sweden in December 2018, January 2019, and January and February 2021, with the assistance of local hunters, and wildlife trackers and staff from five Swedish County Administrative boards ( Figure 1 ). Eurasian lynx regularly move in family groups of females with kittens, and multiple individuals walk in the same footprints (Doran‐Myers et al., 2021). Trackers are skilled at detecting the point at which individuals deviate from shared footprints and form individual tracks. Care was taken to collect tracks most likely to be from single individuals. Fresh snow tracks, together with hair and saliva as positive controls were collected from captive Eurasian lynx at Rauna Zoo, Finland, and Nordens Ark, Sweden. Samples collected from wild lynx were divided into those taken by trained personnel (n = 25) and those taken by untrained personnel and volunteers (n = 19) to assess potential differences in success between the groups. Trained personnel constitute individuals who were provided written protocols and completed a one-hour theoretical training, observed sample collection conducted by experts, and then collected samples under the supervision of trainers. Untrained personnel and volunteers had access to written protocols but did not receive hands-on training prior to collecting samples.

Snow tracks from one snow leopard were collected from Nordens Ark, Sweden in 2021 using fresh snow brought in from a nearby forest. Nasal mucus was collected from the same individual as a positive control.

After snow was melted and filtered, eDNA was extracted from the filters in facilities purpose-built for aquatic eDNA analysis (Bruce et al., 2021), following the ethanol extraction protocol outlined in Spens et al. (2017). Additional steps to the protocol included overnight pooling of the lysate from the pellet in ethanol with the lysate from the filter capsules. DNA was extracted from hair, saliva, and nasal mucus using the Qiagen Blood and Tissue kit following the manufacturer’s instructions. The protocol was modified by adding 70 μl TE buffer pH 8 (Promega, Germany) instead of the AE buffer, heated to 70°C. Samples were stored at -20°C until further processing.

The extracted DNA showed signs of inhibition, so all samples were concentrated and cleaned using the Genomic DNA Clean & Concentrator Kit (Zymo Research, Carlsbad, CA) following the manufacturer’s instructions and using TE buffer pH 8 (Promega, Germany) heated to 70°C. LoBind tubes (Eppendorf, Sweden) were used to avoid DNA absorption into the plastic. We measured total DNA concentrations using the dsDNA Qubit high-sensitivity assay (Thermo Fisher Scientific, Carlsbad, CA) following the manufacturer’s protocol.

The aim of microsatellite analysis from nuclear DNA was to determine whether eDNA collected from snow is a suitable source for future population analyses, and we used a subset of microsatellites to investigate this. For full population analyses, six replicates of each marker and sample would be required to quantify genotyping errors such as allelic dropout and false alleles.

We analysed a total of 30 polar bear samples (24 wild-collected and four captive-collected snow track samples, two positive controls). We pre-screened a subset of samples (n = 5) at 10 polymorphic microsatellite loci that were purpose-designed to maximize genotyping success from degraded DNA (Brandt et al., 2014). PCR products were visualized on a 2% agarose gel. We selected five microsatellites that showed clean bands within the expected allelic size range for genotyping: Uma 14, Uma 40, Uma 42, Uma 73 and Uma 95 (Brandt et al., 2014). Forty-eight Eurasian lynx samples (44 wild-collected and two captive-collected snow track samples, two positive controls) and two snow leopard samples (one captive-collected snow track sample, one positive control) were genotyped at feline microsatellites FCA001, FCA026 and F115 (Menotti-Raymond et al., 1999). All PCRs were run in single-plex format to maximise performance and minimise errors.

PCR amplification conditions following published protocols for polar bears (Brandt et al., 2014) and felid protocols for Eurasian lynx and snow leopards (Menotti-Raymond et al., 1999) resulted in very poor amplification success. Therefore, we adjusted the protocols to include a 2-step touch-down PCR. Each primer set was run in separate tubes and was not pooled during PCR. For all samples, PCRs were performed in 10 μl reaction volumes: 2 × multiplex PCR master mix (Qiagen Multiplex kit), 0.3 μM F and R primer and 2 μl template DNA. Annealing temperatures were initially set at 57°C and decreased (touched-down) by 0.5°C per cycle until 50°C, as follows: 95°C 5 min, 14 (95°C 20 s, 57 – 50°C 30 s, 72°C 20 s), 25 (95°C 20 s, 50°C 30 s, 72°C 20 s), 72°C 5 min. PCR products were then used as template DNA for the second PCR, with amplification conditions of 95°C 5 min, 25 (95°C 20 s, 51°C 30 s, 72°C 20 s) 72°C 5 min.

Final PCR products were visualized on a 2% agarose gel to confirm amplification success and sent to Macrogen Europe for fragment analysis using GeneScan™ GS350 size standard (Applied Biosystems). Three different people visualized and scored the data using the software Peak Scanner 1.0 (Applied Biosystems). Allele boundaries were set at 0.5 bp on either side of allele peaks for dinucleotide repeat loci and 1.0 bp for tetra- and penta- nucleotide repeat loci. Negative controls were included for every tenth sample.

Where full (5-locus) genotypes were obtained for polar bear snow track samples, we used the Matches function for multilocus data in GENALEX v. 6.5 (Smouse and Peakall, 2012) to automatically detect repeated genotypes within the dataset and determine the number of unique and duplicate genotypes.

Total DNA concentrations from snow track samples were low, especially from wild polar bear and Eurasian lynx tracks (polar bear: 0.02 - 7.06 ng/µl, mean 0.92, median 0.37, Eurasian lynx: 0.01 - 32.00 ng/µl, mean 3.83, median 1.18, snow leopard:1.2 ng/µl). We successfully captured nuclear eDNA, verified by microsatellite genotyping, from 87.5% (21/24) of wild polar bear snow track samples, 59.1% (26/44) of wild Eurasian lynx snow track samples, and the single snow leopard sampled ( Table 1 ; Figure S1 ).

Genotyping performance varied among species. Over half of all wild polar bear snow track samples were genotyped across all five microsatellites screened (54.2%, 13/24, Table 1 ), compared with one fifth of wild Eurasian lynx samples genotyped across all three microsatellites screened (20.5%, 9/44, Table 1 ). Snow track samples from captive lynx, the captive snow leopard and three out of four captive polar bears were genotyped at all loci screened ( Table 1 ). All negative controls were negative.

Genotyping success from Eurasian lynx snow tracks was affected by the training level of personnel collecting snow tracks. We retrieved nuclear eDNA from three-quarters (76%, 19/25) of all lynx snow tracks collected by trained personnel, and genotyped around a quarter (24%, 6/25) of samples at three microsatellites. This was significantly higher than for samples collected by untrained personnel and volunteers, where we retrieved nuclear eDNA from 36.8% (7/19) of tracks and genotyped 15.7% (3/19) at three microsatellites (X ^{2 =} 6.85, d.f. = 1, p = 0.01, Table 1 ).

Three wild polar bear and 18 Eurasian lynx snow track samples did not amplify scorable genotypes at any loci. Three wild polar bear snow track samples amplified three alleles at multiple loci, suggesting more than one individual in the sample.

Of the 13 wild polar bear snow track samples scored at all five loci, 11 had unique genotypes. The remaining two samples were identical at all five loci and were collected on consecutive days. Based on this, the 13 snow track samples are likely attributable to 12 polar bears, with one of those bears sampled on two occasions.

For two of the five polar bear microsatellite loci screened, allele sizes were inconsistent with their nucleotide repeat type. Uma 14 (hexanucleotide, (AAATG)₈) and Uma 95 (tetranucleotide, (ATCC)₉) displayed a two base-pair (bp) shift in allele size that was sustained for all subsequent larger alleles.

In Eurasian lynx, locus F115 contained two different allele length ranges, with the majority of alleles between 122-142 bp, alleles at 163 and 169 bp and one allele at 229 bp, expressed as a homozygote in three individuals. This locus has been omitted from previous studies of African lions (Panthera leo) and sequencing of alleles revealed size homoplasy in one (Miller et al., 2014).

Genotypes from hair, nasal mucus and saliva (positive controls) were identical to those from their corresponding snow tracks across all microsatellite loci and species for the paired samples we collected. In these, we did not observe amplification errors that may be indicative of allelic dropout or false alleles across 19 genotypes, of which 10 were heterozygous and nine were homozygous.

Post-sampling challenges of eDNA for population genetic analyses include amplification errors associated with degraded DNA, such as allelic dropout and false alleles (Taberlet and Luikart, 1999; Adams et al., 2019). If not identified and/or overcome, these errors can jeopardize the accuracy of population genetic analyses and subsequent findings related to e.g., parentage and mating systems, species hybridization, and population connectivity (Piggott and Taylor, 2003). Access to captive polar bears, Eurasian lynx and a snow leopard enabled us to preliminarily assess nuclear eDNA integrity from snow tracks by comparing genetic results with corresponding source material, including hair with follicles, saliva and nasal mucus. For all samples across all loci amplified, we retrieved identical genotypes from the snow tracks and their respective positive controls, both for homozygous and heterozygous genotypes: an encouraging result. However, because of the low quantity of DNA we retrieved from snow tracks in the wild, and our small number of positive controls, the risk of amplification error remains and should be accounted for in population genetic analyses that use snow tracks as a source of nuclear eDNA. Following best practices for molecular analyses derived from the fields of forensics, ancient DNA research and non-invasive genetic sampling will help to safeguard against and recognize errors (Piggott and Taylor, 2003; Broquet et al., 2007; Pedersen et al., 2015). Additional screening of known mother-offspring pairs and positive controls could further inform the reliability of snow tracks for microsatellite analyses. Finally, genome-wide protocols for snow samples could help to overcome downstream error specific to microsatellites (Coates et al., 2009).

Carnivore monitoring and conservation requires suitable and efficient sampling protocols (Barea-Azcón et al., 2007). Our study shows that snow tracks have good potential as a reliable source of nuclear DNA compared to other non-invasive sources and could complement conventional sources. The method offers several benefits. Firstly, the non-invasive nature of collecting snow tracks greatly reduces direct disturbance to animals and offers a culturally considerate method of studying populations. Disturbance of polar bears associated with research activities has been cause for concern by some Arctic Indigenous communities, and polar bear snow tracks have already been explored as a non-invasive way to assess individual characteristics (sex and size of bears) through visual assessment by Inuit hunters (Wong et al., 2011; Wong et al., 2017). Secondly, the availability of snow tracks of many species year-round in the Arctic and seasonally elsewhere makes them a promising additional source of nuclear eDNA for population monitoring, especially in regions where few animals but many footprints are observed, e.g., snow leopards in Gansu province, China, and polar bears in Russia-USA (Alexander et al., 2016; Conn et al., 2021). Finally, in our experience, the collection protocol presented, and the materials required to collect snow tracks, should be non-technical enough to be carried out by non-scientists once trained. This study demonstrated the need for investment into appropriate field training of non-professionals, as genotyping success increased substantially when samples were collected by trained personnel, rather than by untrained personnel and volunteers following written protocols alone. Furthermore, individuals who underwent theoretical and technical sample collection training contributed to the improvement of the written protocols through their interactions with trainers over the course of the training. Trainers amended the written protocols based on questions posed by the trainees during the training. Thus, the combination of detailed protocols and interactive field training with experts could broaden the range of end user groups to include hunters, trackers and Indigenous and local community members or volunteers. Snow tracks could be collected by such groups during existing programs, such as annual management inventories of large snow-dwelling mammals and community-based monitoring networks in Arctic sub-regions.

Obtaining estimates of abundance and trends for populations is deemed essential for monitoring responses to climate change (e.g., Vongraven et al., 2012), direct use, and other management measures. Especially if a variety of end user groups could collect snow tracks, genetic mark-recapture databases could be augmented by such sampling, thus achieving more complete representations of populations in time and space. Currently, 10 of the 19 polar bear subpopulations lack the data necessary to determine short-term trends in population status, and only three subpopulations have sufficient data to determine long-term trends (PBSG, 2021). Sampling from snow tracks could also further knowledge of ecological connectivity, which has been identified as a population attribute to understand, maintain and restore, both for snow leopard conservation globally and for Eurasian lynx conservation in Italy and Austria (Li et al., 2020; von Arx, 2020). Finally, as all three species are threatened by conflict with people (human-wildlife conflict, Inskip and Zimmermann, 2009; Clark et al., 2012), sampling of “problem animals” from their snow tracks could help identify and characterize individuals to inform correct management responses.

Total DNA yield from snow tracks was sufficient to capture nuclear eDNA and successfully amplify a selection of microsatellites. Further experimental field work could include determining the minimum number and maximum age of snow tracks required to obtain high quality nuclear eDNA (Hellström et al., 2019; Barber-Meyer et al., 2020), understanding how environmental variables affect DNA from tracks (e.g., high winds, air temperatures, snow types, ultraviolet light exposure) with the aim of producing optimized collection guidelines, and testing the method in wild populations of snow leopards. PCR protocols were adjusted with a two-step PCR to increase success rates in this study, but more optimization of PCR protocols could further improve success. Screening samples at larger panels of microsatellite loci currently used in population genetic analyses of these species would also be informative to precisely compare success rates of snow tracks with other sources of DNA, generate robust genotyping error rates, and assess relative cost-effectiveness of snow tracks with other genetic sampling methods. Finally, familiarizing the method with researchers, managers at local, national and international scales, and people living alongside polar bears, Eurasian lynx and snow leopards, is necessary to mainstream it as an additional tool for conservation and management of these and other snow-living species.