Scottish Wildcat Action (SWA) Specialist Report - Genetics and Morphology

A ‘wildcat’ in this report is defined at level 4 by a cat with a pelage threshold of 17+. Genetic information is not available for all cats and so is not used in population size assessments. 

Background

The Scottish Wildcat Conservation Action Plan (SWCAT) contained a number of project elements and actions and this report addresses the following, for which NatureScot was the partner lead:

Project 3.3: Improve our knowledge of wildcat genetics and taxonomy.

Action 3.3.1:  Assess the correlation between genetic markers and other diagnostic characteristics.

Action 3.3.2:  Assess levels of hybridisation (and disease) in wild populations.

National Lottery Heritage Fund approved purpose:

“To continue monitoring and surveying of wildcat populations in the six priority areas (Pas). Camera-trap images will be screened and analysed. Samples of genetic materials from wildcats and feral cats will be collected to increase knowledge of hybridisation and genetic diversity, as well as disease.”

Summary of work

• Various morphological and genetic methods have been proposed in the past, in order to distinguish wildcats, Felis silvestris, from domestic cats, F. catus, and their hybrids. However, there has often been poor correlation between different methods so that their reliability is uncertain. Here we use genetic and morphological analyses to understand datasets of contemporary and historical wildcats.
• From 2015 to 2019, 118 whole dead cats were collected or made available from a wide variety of sources, including SWA, NatureScot, zoos and members of the public. These were measured, weighed, prepared as skins and skeletons, and samples were taken for subsequent analyses.
• To identify both living and dead specimens of wild-living cats in Scotland, colouration and markings of the fur were used following an analysis of museum specimens by Kitchener et al., (2005), which identified seven key characters of the pelage (7PS score) that distinguish wildcats from domestic cats and hybrids. During morphological analyses, a 7PS of 19+ was used to distinguish wildcats from domestic cats and hybrids in this sample (N.B. a conservative 7PS of 17+ was used to distinguish wildcats in the field, owing to uncertainty in scoring pelage characters).
• Undamaged skulls were scored for five characters to give a total score, the Skull Character Total (SCT) for each cat, which ranged from five (domestic cat) to 15 (wildcat).
• 529 samples were made available for genetic testing, including historic museum skins (n=60), contemporary wild-living dead cats (n=153), captive cats (n=72) and samples from cats that were subject to the TNVR (trap, neuter, vaccinate, return) management scheme (n=1116).
• A genetic test was developed and published, involving the application of 35 Single Nucleotide Polymorphism (SNP) markers, followed by the assignment of a hybrid score called “Q”. Q is an estimate proportion of wildcat ancestry with 0=domestic cat and 1=wildcat. Q has a lower boundary and an upper boundary (LBQ and UBQ, 90% posterior credibility interval). From a genetic management standpoint, cats are considered to be wildcats if LBQ ≥ 0.75, i.e. “pass the genetic threshold”.
• For pelage, the median 7PS of wild-living cats is 10.00 (n=86, range 7-18). Following Kitchener et al., (2005) none of the cats was scored as a wildcat based on pelage (7PS=19+). There was a significant, but weak, correlation with SCT (r² = 0.1539, p=0.018). Median 7PS is 14.00 (n=57) for the period 1960-1995 and four specimens have a 7PS of 19+. For 1960-1995 the correlation between SCT and 7PS is significant (p = 0.0001) and is much stronger (r²= 0.6456).
• Genetic results show that hybridisation between wild-living wildcats and domestic cats in Scotland is extensive, with all datasets of contemporary wild-living cats showing high numbers of hybrids and few or no cats that could be classed genetically as wildcat.
• Both morphological and genetic data show that the current population of wild-living cats in Scotland shows a high level of introgressive hybridisation, with a continuum between domestic cats and the highest scoring hybrids. Historical analyses confirm that hybridisation has been occurring throughout the twentieth century but has increased since around 1995.
• Future conservation management of the wildcat in Scotland relies on the successful release and establishment of captive-bred wildcats with high 7PS and LBQ scores, into areas where future hybridisation with domestic cats and hybrids can be minimised.

Acknowledgements

The SWA project was supported by the National Lottery Heritage Fund.

It was also funded by the Scottish Government, NatureScot and the Royal Zoological Society of Scotland. Support and resources for associated work was also provided by all the Steering Group members: Cairngorms National Park Authority, Forestry and Land Scotland, National Museums Scotland (NMS), Scottish Land & Estates, NatureScot, Scottish Wildlife Trust, The National Trust for Scotland, The Royal (Dick) School of Veterinary Studies, The Royal Zoological Society of Scotland, The Scottish Gamekeepers Association, The Scottish Government, Wildlife Conservation Research Unit (WildCRU). In addition, Jenny Bryce and Fiona Strachan helped develop the project while Eileen Stuart, Alan Bantick and Andrew Kitchener chaired the Steering Group.

Additional sponsors, funders and contributors to SWA work included Aigas Field Centre, Ailsa Black, British Association for Shooting and Conservation, Cairngorm Brewery Company, Chester Zoo, Roy Dennis Wildlife Foundation, John Muir Trust, Loch Lomond & The Trossachs National Park, Lukas Ruiter Production, MyPetOnline, NFU Scotland, petDetect, RSPB, Scotland The Big Picture, Swift Ecology and The Highland Council.

We are also very grateful to the many academics, landowners and managers, farmers, foresters, keepers, captive collection managers, veterinary specialists and others who contributed valuable time and effort, members of the public who contributed funds and support, and in particular the many volunteers who got involved in the project.

SWA project staff (David Barclay, Roo Campbell, Hebe Carus, Calum Hislop, Keri Langridge, Emma Rawling, Nicola Tallach and Matt Wilson) contributed to the collection of, and coordinated the collection of, many samples and specimens analysed in this report. In addition to this, samples and specimens were collected by contractors, vets and researchers including Kerry Kilshaw, Roisin Campbell-Palmer, Kelsey Wilson, Kirstin Mair, Rhian Evans, Alice Bacon, Aberlour Veterinary Centre, Dunnydeer Veterinary Group, Fraser & Fraser Vets, Seafield Veterinary Group, Strathbogie Veterinary Centre and Thrums Vet Group. The authors would also like to thank the many volunteers who handed roadkill wildcat samples to SWA project partners, including NMS, over the years. Without these repeated individual efforts, these types of studies would not be possible. We are extremely grateful for your assistance.

We are also extremely grateful for the assistance of the captive wildcat-holding community in the UK, for their dedicated participation in collecting samples. We thank Louise Tomsett of the Natural History Museum in London and Mark Evans of the New Walk Museum in Leicester for their assistance with accessing historical wildcat material. We thank Danielle Gunn‐Moore at the University of Edinburgh for access to domestic cat reference samples. Laboratory work was conducted by Jennifer Kaden, Muhammad Ghazali and Karen Keegan at the RZSS WildGenes lab, with analysis assistance from Alex Ball. Ben Harrower and Carl Allott are thanked for assistance with visualising/mapping various aspects of genetic data. We thank Phil Bacon for his patience with databasing. We are also extremely grateful to Prof. Ian Jackson of the Medical Research Council Human Genetics Unit for sequencing of the ASIP gene and his informative discussion of black cats.

SNP analysis was funded by the Scottish Government, RZSS and the National Lottery Heritage Fund via grant to NatureScot. Genomic (ddRAD) analysis was funded by RZSS and National Lottery Heritage Fund via grant to NatureScot. All authoring institutions contributed staff time, in kind, to this project.

Specimen measurements, sampling and preparation were carried out by Phil Howard, Georg Hantke and Stephen Rodgers. We are very grateful to the Negaunee Foundation for their continued generous support of Stephen Rodgers as the Negaunee Curatorial Preparator.

Our final thanks to Mark Beaumont and Nobuyuki Yamaguchi for undertaking a critical review of this report.

 

Mean gut length was 1541mm (n=80, s.e.= 43.283, range 497 - 2300mm) [Figure 4] and mean gut index was 3.395 (n=79, s.e.=0.085, range 1.431 - 5.075) [Figure 5]. Excluding kittens (with HB<300mm) [see Figure 6], mean gut length was 1595 mm (n=73, s.e.= 39.434, range 730-2300mm) and mean gut index was 3.293 (n=73, s.e.= 0.080, range 1.431-4.639). Few cats (n=11) had a gut length below 1200mm, which would be characteristic of wildcats (although wildcat gut length may extend to c.1500mm) and there was no evidence for biomodality in gut lengths as would be expected for two distinct species (Figure 4). Gut index also did not show a bimodal distribution (Figure 5) and only 14 animals had a GI of 2.8 or less, which Schauenberg (1977) used to discriminate wildcats from domestic cats. None of these was a wildcat based on 7PS or SCT. The correlation between gut length and head-and-body length (Figure 6; r² = 0.3008) and between gut index and head-and-body length (Figure 7; r² = 0.1059) were weak.

3.2 Genetic results

Results from all 529 samples are presented graphically in Figure 8 and are summarised in Table 1.

Enlarge this image

Analysis of the genetic data revealed a continuum of hybrid scores ‘Q’ for cats sampled in the wild when judged against cats in captivity (35SNP_captive_cats) and historical cats (35SNP_historical_cats). Despite the different methodological approaches used to obtain samples (for example, the 35SNP_SWAScheme_RTA, 35SNP_SWAScheme_Public and 35SNP_SWAScheme_TNVR datasets), the distribution of Q scores is similar. All contain a wide range of hybridised cats.

There is a number of notable cats, which stand out in the dataset and merit being highlighted here.

1. SWA965 (WCQ0515). This cat is a member of the 35SNP_SWAScheme_Public dataset. NMS.Z.2019.72.3. SWCAP 03/2015. Some of the descriptors given in the database include: (Location unknown/ Loch Ard Forest. Juvenile, starved to death.) This has a very high genetic score Q=0.966 (LBQ=0.992, UBQ=1) for a cat of this type. It is the highest of any wild-living cat sampled since 1990. Molecular genetic analysis was repeated for this individual using both 35SNP and ddRAD methodologies, confirming the score for this sample. Pedigree analysis revealed that this cat has a predicted sire/father within the dataset 35SNP_captive_cats. It is possible that this is a cat released/escaped from captivity or that a sample mix-up occurred during the processing of the carcass prior to the sample arriving in the lab (since multiple testing excludes subsequent mix-up). The skin (NMS.Z.2019.72.3) matched to the sample also has a low pelage score of 7PS=14. This cat is discounted from further consideration since its origin cannot be determined with any certainty.
2. SWA258 (WCQ0575). This cat is a member of the dataset 35SNP_SWAScheme_Survey. Q=0.892 (LBQ=0.791, UBQ= 0.972). Location descriptor given in the database “Strathbogie WPA - Clashindarroch Forest”. The cat was given a pelage score of 17. This sample was a non-invasive hair sample and 20% of the genetic profile is missing. There is also another non-invasive sample from the same site (WCQ0576) with a similar score and 42% of the data missing, so it is excluded from the analysis (see Table 1 above, which describes how records were discounted from analysis). Further analysis of new material would be required to confirm these scores.

Below we examine a table of the cats for which the genetic scores were “uncertain” or “pass” (UBQ >0.75, Matrix 1, Senn and Ogden, [2015]) during the course of the study, with their predicted management outcome under the different management schemes operated during the project. Also provided is the actual outcome for that cat.

Table 2: A table of wild-living cats for which genetic scores were “uncertain” or “pass” (UBQ >0.75, Matrix 1, Senn and Ogden, [2015]), during the course of the SWA study. Other cats of Senn et al., (2019) are not examined since sampling was conducted outwith the SWA project. The genetic and pelage score is recorded for each cat. This is then presented with its predicted outcome, as if it had been handled via a management scheme operating during the project:

1. The TNVR management scheme that operated within the Priority Areas (see the TNVR Report)

2. The Captive Breeding Assessment Scheme operated outside of the Priority Areas (Senn and Ogden, [2015], Barclay and Senn, [2021]). The predicted outcome is applied to the samples for which UBQ >0.75 regardless of what dataset it came from. The actual management outcome is then given in the final column. The criteria for predicting the theoretical outcome of this management scheme can be found in “Matrix 1” and “Sub-matrix 2” of Senn and Ogden, [2015].

Table 2: A table of wild-living cats for which genetic scores were “uncertain” or “pass” (UBQ >0.75, Matrix 1, Senn and Ogden, [2015]), during the course of the SWA study. (Download the spreadsheet at the foot of this report)

*Later established same individual as SWA ID 0481 via re-examination of identification of camera trap footage. Roo Campbell pers. coms 07/04/2020. The match is supported by matching genetic profiles.

4. Discussion

4.1 Morphological

The morphological analysis of wild-living cats collected in Scotland by SWA from 2015-2019 showed that the sample is dominated by cats with low pelage scores (7PS) and none could be identified as a wildcat (7PS=19+), with few high-scoring cats (Figure 1).

These contemporary data were compared with two other earlier datasets for cats in museum collections, dating from 1885 to 1959, and from 1960 to 1995. Median 7PS is 14 (n=57) for the period 1960-1995 (Figure 9). Median scores for each pelage character ranged from 2.00 for most characters to 3.00 (nape stripes), so that they ranged across the intermediate score of 2.00. Median SCT is 13.00 (n=105) for the period 1960-1995 (Figure 10). Median scores for each skull character ranged from 2.50 (anterior nasals, nasal length and parietal suture) to 3.00 (angular process), so that all these scores exceeded the intermediate score of 2.00. 

For the period 1960-1995 7PSs were spread roughly evenly across the range of scores and included four animals that were classified as wildcat (i.e. 7PS = 19+) [Figure 9]. However, SCTs appeared to fall into two main groups of higher scoring and lower scoring cats (Figure 10), although this could be a result of sampling error. The correlation between SCT and 7PS is significant (p = 0.0001) and is much stronger (r²= 0.6456) [Figure 11]. Therefore, there has been a deterioration in the correlation between pelage and skull characters between the two time periods, which reflects the loss of high-scoring cats and increased introgression within the hybrid swarm.

This is even clearer when a comparison is made with cats collected between 1885 and 1959 (Figures 12 and 13).  Median 7PS is 21 (n=107) for the period 1885-1959 (Figure 12).  Median scores for the seven pelage characters were all a maximum of 3.00. Median SCT is 14 (n=44) for the period 1885-1959 (Figure 13). Median scores for each skull character ranged from 2.50 (nasal length) to 3.00 (all others), so that all these scores exceeded the intermediate score of 2.00 and were much closer to a maximum wildcat character score of 3.00. The high number of high-scoring wildcats reflects a collecting bias, because domestic cats and obvious hybrids (if present) were not collected and hence are not represented. Even so, the presence of so many high-scoring cats (7PS = 19+) is significant, because so few were recorded in the subsequent time periods (Figs. 1 and 9).

Comparison of median scores for 7PS and SCT for the three time periods shows a dramatic decline (Figures 14 and 15). Although the earlier time period (1885-1959) is not strictly comparable (as it probably excludes hybrids and does exclude feral domestic cats), the other time periods are comparable, because all available cats were collected mainly as road casualties (Figure 16). 

There was no relationship between gut index and 7PS (Figure 17), nor between SCT and gut index (Figure 18), which suggests that there has been a breakdown between the correlation between these two morphological measures in the hybrid swarm. Daniels et al., (1998) found biomodality in gut lengths in wild-living cats in Scotland from the 1990s, which correlated with biomodality in long-bone lengths and differences in pelage characteristics. The frequency distribution was unimodal for the 2015-2019 sample.

A sample of 84 gut lengths from the 1990s has a mean of 1694mm (range 1200-2460mm, s.e. = 31) and mean gut index of 3.185 (range 2.210-5.020, s.e. = 0.070). Comparison of frequency distributions of wild-living cats from the 1990s and 2015-2019 shows that although the recent samples had more shorter guts, there is no significant difference between the frequency distributions (χ² = 23.592, d.f. = 22, p =0.369). 

4.2 Genetics

The data presented here confirms that hybridisation between wild‐living wildcats and domestic cats in Scotland is extensive (Figure 8). Using a 35‐locus SNP test, whose resultant hybrid scores correlate highly with those generated independently from over >3,000 unbiased loci obtained via ddRAD analysis, Senn et al., (2019) demonstrated that contemporary wild‐living cat populations within Scotland consisted of a genetic continuum between F. silvestris and F. catus and that this was not the historical situation. This is backed up by the addition of further contemporary samples from the period 2016-2019 presented in this report (Table 1).

Clearly, it is very hard to unpick the effects of sampling bias, since the motivations and methods for the collection of samples have varied over the years (Table 1). For example, the 35SNP_historical_cats are cats that were shot or trapped in deliberate attempts to target wildcats by gamekeepers, whereas 35SNP_wildliving_dead_cats and 35SNP_SWAScheme_RTA mostly represent road traffic accident victims. Perhaps, on crossing any given stretch of road, wildcats and domestic cats are equally likely to become a fatality, but cats with wildcat‐like tabby pelages may be more likely to be collected by the volunteers who hand the samples in (biasing the sample towards wildcats and hybrids). Conversely, more hybridised and domestic cats may be more likely to be found near busier urban roads, accentuating the bias in the opposite direction (note though that in the Scottish Highlands, many roads cross relatively uninhabited areas). The 35SNP_wildliving_survey_cats sample represents a contemporary sample of cats that was deliberately targeted for their presence in areas of supposed optimal wildcat habitat (Littlewood et al., 2014). This is also the case with the 35SNP_SWAScheme_WildcatTrap cats of this project, and therefore one presumes these might be subject to the same bias as the 35SNP_historical_cats dataset.

However, the 35SNP_historical_cat's dataset is drawn from a more restricted geographical range, with several cats being collected from the southern Highlands (see Figure 1 Senn et al., 2019), thus potentially introducing bias in an unknown direction, as there will undoubtedly be both a spatial and temporal component to hybridisation. The 35SNP_SWAScheme_TNVR dataset was focused on the elimination of threat from feral domestic cats and thus biased towards those cats with lower pelage scores (cats scoring 17+ were released without the opportunity to conduct blood sampling since this would have required veterinary support that was not immediately available).

With these issues in mind, the genetic data are nevertheless strongly indicative that there has been a recent acceleration in hybridisation. Hybridisation has presumably been occurring to some degree since domestic cats arrived on mainland Britain more than 2000 years ago (Macdonald et al., 2010; Kitchener and Daniels, 2010; O'Connor and Kitchener, 2010), although not in all areas at the same time. But these data appear to indicate that within the last decades it has become considerably more common. The basis for this observation rests on the fact that the historical sample set, which results from targeted sampling of wildcats between 1895 and 1985 (35SNP_historical_cats), consists predominantly (54/60) of cats that have an LBQ_35 ≥ 0.75. This is compared to the predominantly-hybrid contemporary sample sets of 1989-2016 (35SNP_wildliving_dead_cats and 35SNP_wildliving_survey_cats) and 2016-2019 (35SNP_SWAScheme_TNVR, 35SNP_SWAScheme_Public,35SNP_SWAScheme_RTA, 35SNP_SWAScheme_Survey, 35SNP_SWAScheme_WildcatTrap), where most cats are hybrids; 106/144 in 1989-2016, and 176/221 in 2014-2019. It is highly unlikely that the distribution of hybrid scores found in the wild in the early to mid‐20th century would have been anywhere close to the continuum seen in these data. Further exploration of the statistical significance of this can be found in Senn et al., (2019). Recent statistical modelling (using approximate Bayesian computation) of this SNP data supports the finding that hybridisation is recent (Howard-McCombe et al., 2021).

The 35SNP_wildliving_survey_cats dataset, whilst representing a targeted and recent sampling of animals from areas thought to contain wildcats in 2014 (Littlewood et al., 2014), has a distribution of Q_35 scores that is only marginally different to those found amongst the road traffic victims in 35SNP_wildliving_dead_cats (D = 0.34737, p‐value = 0.03736). Similar continuous distributions of hybrid scores are found in the datasets 35SNP_SWAScheme_TNVR, 35SNP_SWA_Scheme_Public, 35SNP_SWAScheme_RTA, 35SNP_SWAScheme_Survey and 35SNP_SWAScheme_WildcatTrap, although with the absence of many animals at the higher (wildcat) end of the score.

The low proportion of hybridisation in the captive population (see also Barclay and Senn, 2021) can also be taken as evidence to support the temporal trend apparent in the wild samples, as most of the potential founding animals (with known acquisition dates) to the studbook were taken into captivity in the 1960s and 1970s.

It is worth noting that of the 378 wild-living cats sampled since 1989 (i.e. excluding datasets 35SNP_historical_cats, 35SNP_domestic cats and 35SNP_captive_cats), only 23 cats have a genetic score placing them in the wildcat genetic category (LBQ ≥0.75). Of these, 21 were sampled between 1989 and 2016 and only two cats were sampled subsequently. One cat SWA965 (WCQ0515) has been discussed above and must unfortunately be discounted because of ambiguity over its origin. Another SWA258 (WCQ0575) showed very hopeful scores, although an incomplete profile due to the nature of the sample (hair) cast some uncertainty over them. 

4.3 Morphological and genetics

Correlations between morphological and genetic scores were examined by Senn et al., (2019) in a dataset of 104 cats (Figure 20).

Alt text: A scatter plot of Q to 7PS in a dataset of 104 cats, colour coded by the four dataset. It shows an overall positive relationship between Q and 7PS, but the pattern varies depending on dataset. Most of the samples from captive cats and historic cats show high values for both variables whereas samples from the wildliving dead cat and wildliving survey cat datasets are more widely scattered across the plot with few scoring highly for either variable.

The interpretation of pelage scores against genetic data is clearly challenging. There is a significant relationship between Q_35 (logit transformed) and 7PS pelage. However, the shape of this relationship is difficult to determine and may vary by dataset (Senn et al., 2019). There is no reason why we should expect a simple relationship between Q and pelage scores, and it is in fact likely that this relationship will be complex. Phenotypic traits are likely to be under the control of a small number of genes, some of which may exert dominant effects on phenotype and which will likely interact to produce pelage traits in a non-additive manner. As hybridisation proceeds to introgression we expect a halving of average introgressed ancestry per generation of introgression, until a point where hybrids become so common that they mate with each other and complex hybrids are produced. This is clearly the situation within the contemporary wild datasets. Q scores allow for a relatively simplistic tracking of estimated proportion of ancestry, so that backcrosses cannot be distinguished from more complex hybrids, adding further noise to the relationship since pelage traits will be expected to differ, on average, between backcross generations and other complex hybrid groups. More detailed genomic data, including the sequencing of candidate genes for pelage traits, may help to untangle this pattern. But at least in the short term, it is hard to see how whole or dense genome data will be able to be used in the making of rapid management decisions in the field or during quarantine, although they may become relevant within future management of the captive breeding programme. This genomic analysis of the wildcat is currently underway through a PhD studentship between the universities of Bristol and Cardiff, RZSS and NMS supported by NERC (Natural Environment Research Council) and The People’s Trust for Endangered Species (see also Howard-McCombe et al., 2021).

The TNVR management scheme operated within the Priority Areas (see Trap Neuter Vaccinate Return Programme report) and the Captive Breeding Assessment Scheme (see Conservation Breeding report) operated outside of the PAs (Senn and Ogden, 2015). Table 2 clearly illustrates the challenge of making a binary management decision in situations of elevated hybridisation. However, overall the two different approaches have resulted in consistent judgements across the two management schemes for this subset of borderline genetic cats. In other words, the best genetic cats generally have good pelage scores and have been spared from neutering or being taken into the conservation breeding programme. The exception to this is the case of the black cat 407 (WCQ 0635). This cat was already known to have a borderline Q score and to have produced tabby kittens and therefore did not undergo neutering. The cat was shown to be homozygous for the 2bp deletion in the ASIP gene that is found in domestic black cats (pers.com Ian Jackson, MRC). Thus it is likely to have arrived in the wildcat population via hybridisation (although ancestral polymorphism cannot be ruled out). A decision to release this cat was made due to the uncertainty around the origin of the black variant in the wildcat population. It is still possible that we should consider treating black cats with additional caution during TNVR operations, whilst accepting that they are unlikely to make suitable founders for the captive population due to the likelihood that the black variant is of domestic origin.

A bigger longer-term question is whether further management action should be targeted at wild-living borderline cats with high pelage scores (e.g. WCQ 0925, male), since a similar cat has been accepted into the breeding programme and there is a high likelihood that they will continue to meet and mate with domestic cats or hybrids. Possible options could include semen banking (as attempted by Barclay and Senn, 2021), relocation of cats to safe zones (e.g. release sites of other captive cats or a different PA with other higher-scoring cats), or even their temporary or permanent introduction to conservation breeding facilities. These tough questions lie at the very heart of conservation management of the wildcat in Scotland and complex decisions like these should be made by an appropriate multi-stakeholder body such as the SWA Steering Group.

5. Conclusion

5.1 Morphological

When compared with camera-trap data and live trapping of cats, the range of morphological variation seen in this sample of dead wild-living cats is similar. Therefore, there has been a dramatic decline in the number of wildcats (7PS = 19+) since 1960 until their disappearance in the 21^st century, with decreased correlation between pelage and skull characters in all wild-living cats, which is probably a result of increased introgression within a hybrid swarm (Figure 16).

5.2 Genetic

The data presented here confirms that hybridisation between wild‐living wildcats and domestic cats in Scotland is extensive (Figure 8). Using a 35‐locus SNP test, whose resultant hybrid scores correlate highly with those generated independently from over >3,000 unbiased loci obtained via ddRAD analysis, Senn et al., (2019) demonstrated that contemporary wild‐living cat populations within Scotland consisted of a genetic continuum between F. silvestris and F. catus and that this was not the historical situation. This is backed up by the addition of further contemporary samples from the period 2016-2019 presented in this report (Table 1).

In summary;

• There is very little morphological or genetic evidence for any wildcats remaining in the wild in Scotland.
• Both morphological and genetic data from wild-living cats show a continuum between domestic cats and the highest-scoring hybrid cats.
• Correlation between morphological characters and between morphology and genetics scores appears to have declined during the late 20^th century owing to increasing introgression.
• There is no evidence for viable populations of wildcats in Scotland today, but a few individuals may still occur, which will disappear in the next few years owing to natural mortality and further introgression.
• Future management of wild-living and captive cats in Scotland should, where possible, rely on combined genetic and morphological assessments, owing to high levels of introgression, which creates a difficulty in relying on single characters.
• Overall, TNVR management methods that rely on morphological assessment alone have ensured that the highest-scoring hybrids remain unneutered. However, a more detailed assessment is required as to whether this approach may also be allowing too many genetically-poor individuals to persist in the population, which may compromise the success of releasing captive-bred wildcats for population reinforcement.
• For free-living borderline hybrids with high pelage scores, different management options should be investigated, and an assessment made about how and whether their genetic variation should be preserved. For these options, we will need to consider the availability and quality of captive-bred wildcats for potential reinforcement.

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ANNEXES 1-3

For further information on this report please contact:
Andrew C Kitchener, National Museums of Scotland
National Museums Scotland, Chambers Street, Edinburgh, EH1 1JF
Tel: +44(0) 131 247 4240
Email: [email protected]

This publication is part of a series of specialist reports on the work of the Scottish Wildcat Action (SWA) project that ran from 2015-2020. The work was led and steered by a partnership of organisations: Cairngorms National Park Authority, Forestry and Land Scotland, National Museums Scotland, Scottish Land & Estates, NatureScot, Scottish Wildlife Trust, The National Trust for Scotland, The Royal (Dick) School of Veterinary Studies (R(D)SVS), The Royal Zoological Society of Scotland, The Scottish Gamekeepers Association, The Scottish Government, Wildlife Conservation Research Unit (WildCRU).

Please note that this series of specialist reports was written in parallel and thus minor discrepancies between the sizes of datasets used in different parts of the reports may occur. This document reports on genetic records generated by the Royal Zoological Society of Scotland (RZSS) during the course of the SWA project, joined to metadata as provided by NatureScot in August 2019 from the database SWA_DB_06_Snapshot_20190815.

The many other partners and funders are listed in the SWA Summary report.

For more information contact Martin Gaywood at NatureScot. 

This report, or any part of it, should not be reproduced without the permission of NatureScot or the relevant authors. This permission will not be withheld unreasonably. The views expressed by the author(s) of this report should not be taken as the views and policies of NatureScot. © NatureScot 2023.

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