Mamm Res DOI 10.1007/s13364-015-0253-x
ORIGINAL PAPER
Mapping the spatial configuration of hybridization risk for an endangered population of the European wildcat (Felis silvestris silvestris) in Scotland Kerry Kilshaw 1 & Robert A. Montgomery 1,2 & Ruairidh D. Campbell 3 & David A. Hetherington 4 & Paul J. Johnson 1 & Andrew C. Kitchener 6,7 & David W. Macdonald 1 & Joshua J. Millspaugh 5
Received: 10 June 2015 / Accepted: 20 October 2015 # Mammal Research Institute, Polish Academy of Sciences, Białowieża, Poland 2015
Abstract The wildcat in Scotland, UK, is currently at risk of extinction because of hybridization with feral domestic cats (ferals) and hybrids (wildcat × domestic cat crosses). Conservation efforts are hampered by limited information on the distribution of these three cat types and the spatial variation in hybridization risk. From January 2010 to July 2013, we conducted widespread camera-trapping surveys throughout northern Scotland to document the distribution of ferals, hybrids, and wildcats. Using single-season occupancy models, we predicted the probability of occupancy for these three cat types across Scotland. Over 49,031 camera-trapping days, we had 87 captures (photo of a cat at a camera-trap station within Communicated by: Krzysztof Schmidt * Kerry Kilshaw
[email protected] 1
Wildlife Conservation Research Unit, Recanti-Kaplan Centre, Tubney House, Department of Zoology, University of Oxford, Abingdon Road, Tubney, OX13 5QL Oxon, UK
2
Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, 13 Natural Resources Building, East Lansing, MI 48824, USA
3
Royal Zoological Society of Scotland, Edinburgh Zoo, Edinburgh, Scotland EH12 6TS, UK
4
Cairngorms National Park Authority, 14 The Square, Grantown on Spey, Scotland PH26 3HG, UK
5
Department of Fisheries and Wildlife Sciences, University of Missouri, 302 Natural Resources Building, Columbia, MO 65211, USA
6
Department of Natural Sciences, National Museums Scotland, Chambers Street, Edinburgh EH1 1JF, USA
7
Institute of Geography, School of GeoSciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, UK
a 24-h period) of wildcats, 145 captures of hybrids, and 193 captures of ferals. At over 48 % of the camera-trap stations where we detected wildcats, we also detected ferals or hybrids. We predicted wildcat occupancy as a function of habitat covariates. Wildcat occupancy probability increased in habitat with a higher proportion of mixed woodland habitat and decreased in habitat with more edge (transition from closed to open habitats). Hybrids showed a clear overlap in their distribution pattern with both ferals and wildcats. The results indicate that wildcats in Scotland are at risk of hybridization across much of their current distribution from ferals and/or hybrids. In particular, hybrids have an increased probability of occupying much of the same habitat as wildcats compared to ferals, supporting recent suggestions that hybrids may pose a significant additional hybridization threat by facilitating gene flow between wildcats and ferals. Keywords Camera-trap . Distribution . Felis silvestris silvestris . Hybridization . Occupancy . Wildcat
Introduction One of the greatest global threats to persistence of native species is hybridization (Allendorf et al. 2001), which may result in genetic extinction through introgression and can be particularly problematic for isolated and rare indigenous species (Levin 2002; Rhymer and Simberloff 1996). In some cases, distinct indigenous populations interact with closely related domestic animals, whose populations have largely been anthropogenically fostered. Such is the case for European wildcats, Felis silvestris silvestris, across their range (Oliveira et al. 2008; Pierpaoli et al. 2003; Randi et al. 2001). The genetic integrity of European wildcat populations is threatened both
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by the loss of allelic variation due to genetic drift and by the introgression of genes from roaming or feral domestic cats (Stahl and Artois 1991). Hybridization, therefore, has been identified as one of the greatest threats to wildcat persistence (Stahl and Artois 1991), having already resulted in the local extirpation of some European wildcat populations (Suminski 1962). Given the risk of species extinction from hybridization, for effective conservation initiatives, it is essential to determine factors associated with spatial overlap between wildcats and domestic cats (F. catus). Mapping species distributions is an important component of biodiversity management and conservation (Peterson et al. 2011), but often difficult to achieve, particularly for species which are challenging to survey or for which limited information exists (Rushton et al. 2004). The Scottish population of the European wildcat was previously widespread across Britain but suffered from heavy persecution and extensive habitat loss and is now restricted to parts of northern Scotland (Balharry and Daniels 1998; Davies and Gray 2010; Easterbee et al. 1991). By extrapolation from wild-living cat specimens collected in the 1990s, the population of wildcats in the mid-2000s was estimated to be c. 400 individuals (Macdonald et al. 2004). However, this estimate is likely no longer accurate as wildcats in Scotland, like European wildcats across their range, are increasingly threatened by hybridization with feral/domestic cats (Hubbard et al. 1992; Macdonald et al. 2004; Nowell and Jackson 1996). Hybridization with feral/domestic cats threatens the genetic integrity and evolutionary persistence of wildcat populations (Pierpaoli et al. 2003; Randi et al. 2001), particularly in Scotland, which has one of the highest levels of hybridization (Oliveira et al. 2008). Because hybridization has complicated wildcat survey and monitoring efforts across its range, limited data exist on both the spatial distribution and environmental factors that might influence wildcat occupancy (Macdonald et al. 2004). Between 2010 and 2013, we implemented camera-trap surveys across northern Scotland to detect wildcats, feral/ domestic cats (hereafter referred to as ferals), and wildcat× domestic cat hybrids (hereafter referred to as hybrids). Camera-trapping has been used to successfully survey for the wildcat in Scotland, Sicily, and Portugal (Anile et al. 2007, 2009; Kilshaw et al. 2015; Monterroso et al. 2009), and occupancy models, which can be used to draw inferences about habitat use and selection and predict species occurrence at multiple scales (MacKenzie et al. 2006), have recently been used to predict the distribution of elusive species from cameratrap data (Cove et al. 2013; O’Brien 2008). Using camera trap data and occupancy modeling, we aimed to (i) map the probability of occurrence for these cats throughout Scotland, (ii) identify habitat covariates associated with the occurrence of these cat types, and (iii) determine the degree of similarity of these animal-habitat relationships among these cat types. These objectives serve the purposes of documenting the
potential distribution of the wildcat and quantifying the spatial configuration of hybridization risk in the landscape.
Materials and methods Study area We conducted this study across the Scottish Highlands (∼50, 000 km2), a large area of mainland Scotland, north of the Highland Boundary Fault (Fig. 1). Within the study area, climate and habitat vary significantly from east to west, with large bodies of water (lochs) breaking up the landscape. Winter snowfall is common across the region, particularly on high ground in the east. The west has a milder climate but typically receives more rainfall (MET 2012). Human population density is low by European standards, with an average of 0 of encountering a camera-trap station. At one site (M), we deployed only four camera-trap stations due to access limitations (Table 1). As part of a different study (Hetherington and Campbell 2012), two separate cameratrap sampling sessions were conducted at five sites (A, B, C, D, and I) across the 4-year period (Table 1). During the second sampling session, camera-trap stations at site A were positioned in different locations within the site. Thus, this second survey was treated as a separate site in this analysis. Cameratrap stations were placed in habitat associated with signs of either wild-living cats or potential indicator species of cats. Cat signs included footprints, scats, dens, scrape marks, or recent sightings, while indicator species included pine martens (Martes martes), which have similar habitat and prey requirements to the wildcat (Balharry 1993; Birks et al. 2005), or
Mamm Res Fig. 1 Distribution of cameratraps in Scotland for the detection of wildcats, hybrids, and ferals, 2010–2013 at sites A–AA
rabbits (Oryctolagus cuniculus), the wildcats’ preferred prey species (Hubbard et al. 1992; Lozano et al. 2006; Malo et al. 2004). At each station, we deployed two camera-traps, either Cuddeback Capture 3.0 (Cuddeback IR Cuddeback Digital, Green Bay, Wisconsin, USA) or Reconyx HC500 IR (Reconyx, Inc., Holmen, Wisconsin, USA). We positioned camera-traps facing each other across obvious animal trails but slightly staggered to avoid flashes interfering with photos from opposite cameras to ensure that both sides of cats were photographed for identification purposes. We attached camera-traps to suitable trees or fence posts 20–50 cm above ground level, to achieve the best angle for photographing pelage characteristics. Each camera station was baited with dead pheasant (Phasianus colchicus) or red-legged partridge (Alectoris rufa) and a scent lure to help attract wildcats to the cameras. We tied bait to the top of a 1-m wooden stake driven into the ground between the two camera traps. Following studies on European wildcats (Weber 2008), undiluted valerian tincture (AVogel/Holland & Barrett) was smeared onto the lower third of the stake. Camera-traps were active for 60–80 days/sampling session and were checked every 10–14 days to replace bait and lure, check batteries, and download photographs. Cats were categorized as feral, hybrid, or wildcat based on Kitchener et al. (2005). Cats were given a total score for seven key pelage characteristics (7PS; neck stripes, shoulder stripes, percentage of broken stripes on flanks and hindquarters, spots on flanks and hindquarters, extent of dorsal line, prominence of tail rings, and shape of tail tip), with each characteristic given a score of 1 for Bdomestic,^ 2 for intermediate, and 3
for Bwildcat^ traits. An additional eight pelage characteristics (white on chin, white on flanks, white on paws, stripes on cheek, spots on underside (not always possible to score from camera-trap photos), color of tail tip, number of stripes on hind leg and ear color) were also scored to provide further support for identification purposes. Cats with a 7PS of ≥14 and no scores of 1 (domestic traits) for any of these 15 pelage characteristics were identified as wildcat unless any other evidence suggests, otherwise, e.g., it is clearly a domestic pet. The threshold score is the Brelaxed^ wildcat defined in Kitchener et al. (2005), used as a precautionary approach because not all pelage characters could be determined from camera-trap photographs. Habitat covariates We developed a geographic information systems (GIS) database of habitat covariates expected to influence the occupancy of these three cat types based on published resources and a priori rationale. In order to map their occurrence throughout Scotland, we represented each individual habitat covariate as a raster, a collection of spatially-explicit cells expressing attributes of the landscape, at a resolution of 500 × 500 m (0.25 km2). We intersected the camera-trap locations with the habitat rasters to populate our database for statistical analysis. Previous surveys have demonstrated that wildcats select for habitat patch mosaics consisting of open fields, particularly those that support rabbits and small mammals, and forested patches, while avoiding mature conifer plantations, open
Nov 2010–Feb 2011, Nov 2011–Feb 2012 Feb–May 2011 Jan–April 2012
C
May–June 2012
June–Sept 2012
Oct 2012–Jan 2013
Oct–Dec 2012
Nov 2012–Jan 2013
Nov 2012–Jan 2013
Dec 2012–Feb 2013
Dec 2012–Feb 2013
Jan–April 2013
Feb–April 2013
Feb–April 2013
Feb–May 2013
Feb–May 2013
Feb–May 2013
April–July 2013
M
N
O
P
Q
R
S
T
U
V
W
X
Y
Z
AA
Total Jan 2010–July 2013
March–June 2012
L
20
Nov 2011–Mar 2012
Jan–April 2012
Feb–April 2011 Jan–March 2012
I
J
Sept–Nov 2011
H
K
20, 20
June–Oct 2011
G
526
21
20
20
20
20
20
20
20
20
20
20
20
20
21
4
20
20
20
20
20
20
March–June 2011
May–August 2011
E
20, 20
20, 20
F
D
Jun–Dec 2010, Aug–Nov 2011 20, 20
B
20, 20
Jan–May 2010, Nov 2011–Jan 2012
A
Wildcat
0
0
0
20
49 031
1800
1376
1622
2013
1440
1342
1410
1514
1257
1285
1459
1468
1318
1589
132
1478
1914
2162
65
0
0
0
9
0
0
0
0
0
0
0
0
0
1
0
0
0
3
1274, 1439 0
1278
2016
1532
1327
1604, 1468 19
1685, 1347 0
3514, 1751 2
94
0
1
0
20
0
7
6
0
0
0
0
0
0
2
2
0
0
5
9
0
0
0
1
18
10
4
9
Hybrid
132
0
0
0
23
2
2
4
5
2
0
2
0
0
16
5
12
10
1
3
0
0
0
9
2
14
20
0
Feral
No. captures/7-day bin period
1989, 1319 11
No. camera trap TN stations
Sampling periods
2–802
145–434
59–314
4–278
271–610
29–190
17–299
20–301
62–122
257–469
39–357
75–414
25–545
68–343
2–301
6–185
3–369
7–613
180–431
307–557
81–415
241–802
111–214
203–372
191–451
175–480
278–421
280–400
0.00–2.27
0.00–1.08
0.00–0.62
0.00–1.25
0.00–1.76
0.00–2.08
0.00–1.51
0.00–1.61
0.00–0.56
0.06–1.57
0.00–1.31
0.00–2.27
0.00–1.42
0.00–0.83
0.00–0.55
0.17–1.47
0.00–1.78
0.00–1.38
0.00–1.24
0.00–1.05
0.00–1.25
0.00–1.38
0.00–0.86
0.00–1.47
0.00–0.94
0.00–1.92
0.05–0.98
0.00–1.64
0.01–13.86
0.64–4.05
2.56–6.32
0.09–6.06
0.91–5.26
0.09–2.83
0.16–2.75
0.16–3.05
0.82–4.51
0.87–4.48
0.19–2.53
0.41–5.07
0.52–4.74
0.04–3.36
0.17–4.20
0.32–1.61
0.07–3.80
0.01–6.93
1.64–5.03
1.62–5.30
0.09–8.51
0–0.35
0–0.27 0–0.56
0–0.66 0–0.66
0–0.03 0–1
0–0.04 0–0.52
0–0.57
0–0.77
0–0.62
0–0.37
0–0.53
0–0.37
0–0.15
0–0.38
0–0.16
0–0.78
0–0.85
0–0.82
0–0.88
0–0.32
0–0.62
0–0.72 0–1
0–0.02 0–0.75
0
0
0
0–0.72 0–0.81
0–0.21 0–0.80
0–0.53 0–0.42
0
0
0–0.21 0–0.69
0–0.05 0–0.97
0–0.02 0–0.83
0
0–0.08 0–0.81
0–0.65
0–0.30
0–0.3
0–0.26
0–0.12
0–0.24
0–0.58
0–0.47
0–0.06
0–0.28
0–0.06
0–0.65
0–0.50
0–0.33
0–0.41
0–0.06 0.03–0.38 0–0.16
0–0.05 0–0.88
0
0–0.17 0–0.81
0
0
0
0–0.29
0–0.16
0–0.09
0–0.23 0.08–0.93 0–0.17
0–0.03 0–0.88
0–1
0.08–1
0–1
0–0.21
0–1
0.12–1
0–1
0–0.93
0–1
0.04–0.99
0–0.98
0–0.93
0–0.37
0–0.05
0–1
0.02–0.86
0–0.96
0–0.45
0–1
0–0.80
0–1
0–0.48
0.44–1
0–0.91
0–0.94
0–1
0–0.9
0–0.94
0–0.88
0–0.62
0–0.81
0–0.57
0–0.77
0–0.86
0–0.56
0–0.66
0–1
0–0.52
0.08–0.93
0–0.88
Gorse
0–1
0–0.47
0–0.95
0–0.90
0–0.52
0–0.02
0–0.47
0–0.90
0–0.14
0–0.73
0–0.99
0–0.60
0–0.97
0–0.90
0–0.43
0–1
0–0.75
0–0.88
0–0.32
0–0.62
0–0.81
0–0.80
0–0.42
0–0.85
0–0.82
0–0.69
0–0.96
0–0.82
0–0.78
0–0.81
0.01–0.08 0.03–0.38
0–0.30
0–1
0–0.35
0–0.57
0–0.35
0–0.72
0–0.11
0–0.13
0–0.50
0–0.44
0–0.29
0–0.77
Arable Grassland Mixed Coniferous Heather woodland woodland
Proportion of habitat cover/500 m2
11.19–13.86 0–0.02 0–0.86
0.97–3.15
0.9–3.03
1.32–6.73
0.85–4.67
0.7–4.76
0.53–2.48
Elevation (m) Amount of Distance to edge (km) urban (km)
Summary statistics of trapping periods, number of traps, trap nights (TN), camera-trap events, and habitat conditions at the sites surveyed
Site
Table 1
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pasture, heather moorland, and areas of intensive agriculture (Corbett 1979; Easterbee et al. 1991; Daniels 1997). Gorse also appears to be important, at least in west Scotland (Scott et al. 1993). In addition, favorable environmental conditions include areas of high altitude (100–650 m), cold climate (e.g., mean minimum annual temperature of −5–10 °C), and low human population densities (20 % broadleaved trees and combined into a category called mixed woodland), coniferous woodland, arable/horticultural areas, improved grasslands and seminatural grassland (combined into a single category referred to as grassland), gorse (Ulex europaeus) scrub, and dwarf shrub heath (heather and heather grassland) (Table 1) giving a total of six habitat covariates. Because data describing the distributions of potential wildcat prey were not available at the spatial extent of Scotland, we tested the effect of edge habitat (the transition from closed to open habitat) as a proxy for wildcat hunting
habitat (see Jerosch et al. 2010; Klar et al. 2008; Silva et al. 2013). First, we created a binary vector layer representing Bopen^ (gorse, dwarf shrub heath, and seminatural grasslands) and Bclosed^ (deciduous, coniferous, and mixed) habitats; then, we intersected this binary layer with the 0.25-km2 grid lattice and calculated the linear length (km) of habitat where open and closed habitats abutted. No evident collinearity (|r|≥0.70) was found amongst our predictor covariates. Modeling design We developed separate occupancy models to estimate occurrence of ferals, hybrids, and wildcats. Using camera-trap data, we created occupancy matrices that depicted presence/ absence of each cat type across our study period, where every cell in the matrices was coded as 1 (presence), or 0 (absence), or as NA (no survey was conducted or camera-traps were inactive due to either battery failure or snow cover) at a resolution of one trapping day. We binned data into 7-day periods to improve computation and because of low detection rates of each cat type (see Ahumada et al. 2013). We fitted single-species single-season site occupancy models (MacKenzie et al. 2002) to predict the occupancy probability for each cat type using the UNMARKED package in R (R version 3.02.0, , accessed 1 May 2014 Fiske and Chandler 2011). These models have two important assumptions. Firstly, to separately estimate the probabilities of detection and occupancy, replicate surveys must be conducted among sites. Secondly, species occupancy at a site is expected to remain constant throughout the study period. In our analysis, no site was open for >6 months consecutively. We could not fit dynamic multiseason occupancy models (Kéry et al. 2013) to these data, because our data collection efforts were temporally staggered across sites due to the logistical constraints of maintaining numerous cameratrap stations across northern Scotland (Fig. 1). Therefore, we did not consider the temporal dimension of the dataset, which still permits modeling of the spatial variation in cat occurrence. Model selection We developed a two-stage model selection process to identify the most parsimonious models, using Akaike Information Criterion (AIC), and then ranked model support using AIC weights (AICω) (Burnham and Anderson 2002). In the first stage, we identified the most suitable model structure among three types: (1) a model where occupancy ( ), colonization (γ), extinction (ε), and detection (p) are held constant, (2) a model where the detection process is allowed to vary with time, and (3) a model
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where the occupancy process varies as a function of habitat covariates and the detection process is time-varying (e.g., Kéry et al. 2013). In this case, we modeled the linear and quadratic effects of the camera-trap survey date (using the day of the year at the start of each 7-day survey period) on the detection probability (Kéry et al. 2013). In all cases, the most supported model, derived from the first stage of the model selection process, was a model with a time-varying detection process and a habitat covariate-varying occupancy process (see Table 2). With this top-ranking model in place, we then evaluated models built from all combinations of habitat covariates that were believed to affect the occupancy of ferals, hybrids, and wildcats (i.e., a priori rationale; see Table 3). After ranking model support for each cat type, we calculated average models within a cumulative AICω of 0.95 to produce final unconditional parameter estimates, using the AICcmodavg package in R (Burnham and Anderson 2002; Mazerolle 2014). We assessed the relative importance of each habitat covariate by calculating a summed AIC weight (∑AICω) across those models within a cumulative AICω of 0.95 (Burnham and Anderson 2002; Symonds and Moussalli 2011). ∑AICω≈1 indicates that the habitat covariate is highly supported, and ∑AICω≈0 indicates little support. We used the unconditional parameter estimates to map predicted probability of occurrence for each cat type. These maps were rasters representing the predicted probability of cat occurrence (wildcat, hybrid, and feral) across Scotland at a resolution of 0.25 km2 (Fig. 2). Studies have indicated that for European wildcats, the probability of wildcat habitat use decreases at distances less than 900 m from villages and 200 m from single houses, although the exact critical distance is dependent on the particular habitat (Klar et al. 2008). Further, high elevation areas (>800 m) are also considered to be unsuitable for these three cat types (e.g., Easterbee et al. 1991; Daniels 1997), and no areas above 802 m were surveyed. Thus, we excluded from these predictions of cat occurrence habitat 800 m in elevation (unsuitable habitat for all cat types) is represented in white. Because of the lack of wildcats south of the Central belt (lying between Glasgow and Edinburgh), the data shown here represents habitat suitability rather than true occupancy probability
Our wildcat occupancy predictions support other studies on European wildcats that suggest they require habitats that provide shelter and resting places (e.g., woodland) and more open patches for hunting (e.g., open fields or riparian areas) (Biró et al. 2004; Corbett 1979; Stahl et al. 1988; Wittmer 2001). For example, European wildcats tend to be associated with forests, reaching their highest population densities in broadleaved or mixed forests (Parent 1975; Schauenberg 1981; Stahl and Leger 1992), but appear to avoid large, homogenous coniferous forests (Castells and Mayo 1993), probably due to lack of prey diversity and abundance (Easterbee et al. 1991). In Scotland, studies showed that wildcats select habitat mosaics consisting of open fields and reforested patches (Easterbee et al. 1991) and tend to use woodland and stream edges, while avoiding heather moorland (Daniels 1997), although Daniels (1997) noted that they avoided open pasture, in contrast to Easterbee et al. (1991). Also in north-east Scotland, Corbett (1979) found that wildcats used forests but avoided mature pine forests, and in western Scotland, Scott et al. (1993) reported that wildcats occurred in woodland and gorse scrub in relation to its availability within their home ranges. Factors that might influence feral and hybrid occurrence have been largely unstudied in Scotland, although ferals were positively associated with farm buildings in winter and spring (Daniels 1997), where they were likely scavenging or preying on commensal rodents when rabbits are less available (Corbett 1979). In Scotland, arable farmland is frequently interspersed with patches of woodland and grassland, providing a mosaic of cover, including edge habitat with suitable prey for cats. Farm buildings, especially in winter, provide suitable cover for ferals and hunting opportunities (Germain et al. 2008). Our results support observations of ferals tending to remain near (
