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Volume 82, Issue 1


Home-range size of the European wildcat (Felis silvestris silvestris): a report from two areas in Central Italy

Stefano Anile
  • Corresponding author
  • Dipartimento di Biologia Animale ‘Marcello La Greca’, Università di Catania, Catania, Italy
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/ Lolita Bizzarri
  • Dipartimento di Chimica, Biologia e Biotecnologie, Università degli Studi di Perugia, Perugia, Italy
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/ Moreno Lacrimini
  • Dipartimento di Chimica, Biologia e Biotecnologie, Università degli Studi di Perugia, Perugia, Italy
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/ Andrea Sforzi / Bernardino Ragni
  • Dipartimento di Chimica, Biologia e Biotecnologie, Università degli Studi di Perugia, Perugia, Italy
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/ Sebastien Devillard
  • Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, CNRS, UMR5558, F-69622, Villeurbanne, France
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Published Online: 2017-03-02 | DOI: https://doi.org/10.1515/mammalia-2016-0045


Although the behavioural ecology of the European wildcat (Felis silvestris silvestris) has been studied in several European countries, its home-range size is still poorly known due to elusive behaviour of the species living in typically low population densities. In our study, 11 wildcats from two distinct areas, the Maremma Regional Park (Tuscany; 3 males and 1 female) and the Paradiso di Pianciano Estate (Umbria; 6 males and 1 female), both located in Central Italy, were studied by means of classical VHF radio-tracking. Home ranges were calculated by means of the Brownian bridge movement model (BBMM). Variables significantly affecting home-range size were: study area, gender and the interaction between gender*age. The potential effect of the reproductive season and the nocturnal period was not supported. The main findings indicate that: (1) home-range sizes in Tuscany were larger than those in Umbria; (2) home-range size was positively related to the age of individuals; (3) males exploited larger home ranges than females in all age-classes except for the sub-adult age-class; this latter pattern has never emerged from any previous wildcat radio-telemetry study. Population density, different management regimes in the areas considered and the local abundance of prey may explain differences in home-range sizes between the study areas. The estimated home ranges of wildcats in Umbria were slightly larger than those reported across Europe, while those calculated in the Tuscan study area were significantly greater.

This article offers supplementary material which is provided at the end of the article.

Keywords: Brownian bridge movement model (BBMM); European wildcat; general additive mixed model (GAMM); home-range; Italy; radio-tracking


The European wildcat (Felis silvestris silvestris) is a small felid (body weight: 3–5 kg) (Ragni 1981, Kery et al. 2011) which is widely distributed throughout Europe, from Sicily to Scotland and from Portugal to the Caucasus (Nowell and Jackson 1996). Although the species is currently classified as being of “Least Concern” by the IUCN (data access 17/07/2015), many wildcat populations are shrinking, especially in southern regions (Yamaguchi et al. 2015). The chief threats to the long-term conservation of the European wildcat are: habitat fragmentation (Ragni 1981, 2006, Say et al. 2012), human-induced mortality (Ragni 2006, Klar et al. 2009, Lozano and Malo 2012) and hybridisation with the domestic cat (Felis silvestris catus) (Randi et al. 2001, Ragni 2006, Oliveira et al. 2008a). Locally, the overgrazing of wild ungulates (Sus scrofa and Cervus elaphus) (Lozano et al. 2007) and the presence of humans (Piñeiro et al. 2012) may also impact negatively on wildcat populations.

Italy hosts at least three geographically distinct wildcat populations (Mattucci et al. 2013), with some territories (namely in the North-West Apennines) having been recently recolonised (Velli et al. 2015). The general trend of the population can be considered stable at the national level. However, wildcat studies (and ensuing conservation measures) have been relatively scarce in Italy, resulting in a general lack of knowledge of wildcat ecology and behaviour.

Assessment of the animal’s spatial behaviour is a crucial initial step in order to undertake the action needed to conserve wildcat populations throughout their range (Birò et al. 2004, Sarmento et al. 2006, Monterroso et al. 2009). Species-specific home-range size is a key parameter in numerous frameworks, such as landscape genetics (e.g. calibration of uncertainty for spatial genetic analysis; Mattucci et al. 2013), population estimates (e.g. calibration of camera-trap spacing within study areas; Anile et al. 2014) and habitat modelling (e.g. as a response variable in modelling analysis; Germain et al. 2008, Klar et al. 2008, Monterroso et al. 2009).

To date, radio-telemetry studies on the home-range size of the European wildcat have been undertaken in several European countries, such as France (Germain et al. 2008), Scotland (Corbett 1979, Scott et al. 1992, Daniels et al. 2001), the Iberian Peninsula (Sarmento et al. 2006, Monterroso et al. 2009, Soto and Palomares 2013), Hungary (Birò et al. 2004) and Germany (Wittmer 2001). Notably, however, radio-telemetry studies are lacking in Italy. More importantly, owing to the elusive behaviour of the species and the typically low population densities (in addition to the cost and feasibility of radio-tracking), very few studies with a sample size of 10 or more animals have been conducted (Corbett 1979, Stahl et al. 1998). The home range of the wildcat has been seen to vary greatly among the areas studied. Males usually exploit larger areas than females, with low or null overlapping among males and different degrees of overlapping among females and between males and females (Corbett 1979, Stahl et al. 1998, Wittmer 2001, Birò et al. 2004, Germain et al. 2008). Moreover, home-range size can also be affected by the age of the animals, with juveniles and sub-adults of both sexes using smaller home ranges than adults (Corbett 1979, Daniels et al. 2001, Monterroso et al. 2009). Finally, wildcats typically display crepuscular/nocturnal peaks of activity (Corbett 1979, Daniels et al. 2001, Germain et al. 2008) and can travel long distances at night (Wittmer 2001). Indeed, most of the day they spend in well-characterised resting places (Corbett 1979, Jerosch et al. 2010). Diurnal home ranges can therefore be expected to be smaller than nocturnal ranges.

In the current study, we aimed to

  1. contribute to filling the gap in the ecology (specifically, the home-range size) of the wildcat in Italy by analysing the spatial behaviour of wildcats in two distinct areas of Central Italy: the Maremma Regional Park (MRP) in Southern Tuscany and the Paradiso di Pianciano Estate (PPE), a private game reserve in Umbria. Specifically, we sought to estimate the home range of the wildcat both on a yearly basis and during the reproductive season, and to identify which variables (e.g. study area, gender and age) significantly affected the wildcat’s home-range size.

  2. On the basis of the above-mentioned behavioural traits (marked nocturnal activity and the use of daytime resting sites), we aimed to ascertain whether there was a difference between nocturnal and diurnal home-range sizes.

Materials and methods

Study areas

We assumed that the catch-ability of wildcats was equal in both our study areas (see also Results section, below). Thus, our observation that trap rates (#wildcats/trap-days) were higher in the PPE than in the MRP (4/1516=0.0026 vs. 11/3352=0.0033), as was the number of cats per trapping area (#wildcats/trapping area calculated as the minimum convex polygon: 4/7022=0.0005 vs. 11/3590=0.0031), prompted us to hypothesise that wildcat population density differed between the two study areas. In addition, the MRP hosts a relative recently established population, as a direct result of a reintroduction project carried out from the late 1980s to the mid-1990s (Ragni et al. 2007, Sforzi et al. 2010), whereas the PPE is located within a core area of species distribution in the Apennines. Finally, our study areas also differ in terms of management regimes, the MRP being a national park (tourism) while the PPE is a private game estate (hunting).

The MRP is located on the Tyrrhenian coast in southern Tuscany (Grosseto Province) (Figure 1) and covers an area of approximately 10,000 ha, ranging from 0 to 417 m. a.s.l. The typically Mediterranean local climate is characterised by a dry, warm spring-summer period and a rainy, mild autumn-winter period. Mediterranean oaks (Quercus ilex and Quercus suber) grow in most of the hilly areas, while the plain-coastal areas are characterised by pine woodland (Pinus pinea and Pinus pinaster), scrub, garigue and marshland. The PPE is a 7200 ha hilly-mountainous portion (400–1354 m a.s.l.) of the Umbrian Apennines (Figure 1) and is managed as a “private game estate”. The climate is temperate-continental, with a wet, warm summer-autumn period and a wet, cold winter-spring period and annual snowfalls. Deciduous broad-leaf forest (Ostrya carpinifolia, Quercus cerris, Fagus sylvatica) covers 69% of the land area, while the remainder comprises secondary grassland (15%), olive-groves (6%), cropland (7%), sclerophyll woods and hedges (3%). The mammalian fauna of both areas includes: the wild boar (Sus scrofa), roe deer (Capreolus capreolus), red fox (Vulpes vulpes), wildcat, badger (Meles meles), stone marten (Martes foina), brown hare (Lepus europaeus), crested porcupine (Hystrix cristata), red squirrel (Sciurus vulgaris), common dormouse (Muscardinus avellanarius), wood mouse (Apodemus sylvaticus) and black rat (Rattus rattus). The fallow deer (Dama dama), pine marten (Martes martes), coypus (Myocastor coypus), house mouse (Mus musculus) and brown rat (Rattus norvegicus) are only present in the MPR, while the Apennine wolf (Canis lupus italicus), polecat (Mustela putorius), edible dormouse (Glis glis), garden dormouse (Eliomys quercinus), bank vole (Clethrionomys glareolus) and yellow necked mouse (Apodemus flavicollis) are only present in the PPE.

Map showing the location of the two study areas and wildcat distribution in Italy (modified from the IUCN red list). Black: settlements and roads; dark grey: woodland; mid grey: marsh vegetation; pale grey: grassland; white: cropland.
Figure 1:

Map showing the location of the two study areas and wildcat distribution in Italy (modified from the IUCN red list).

Black: settlements and roads; dark grey: woodland; mid grey: marsh vegetation; pale grey: grassland; white: cropland.

Trapping and radio-tracking

Trapping sessions were undertaken from April to June 1995 and from February to November 1999 in the MRP and from June 2003 to June 2006 in the PPE. Traps were checked once a day, at sunrise, (see details in Bizzarri et al. 2010). Morphological identification and assignment to the European wildcat were performed on the basis of coat pattern markings (Ragni and Possenti 1996). Blood samples were taken for genetic identification (Mattucci et al. 2013). Trapped wildcats were anaesthetised in accordance with standard procedures (Bizzarri et al. 2010). For each wildcat, the following data were recorded: gender, weight and approximate age (juvenile=0–12 months; sub-adult=12–24 months; adult>24 months), as estimated by visual inspection of body size and structure and the degree of emergence and integrity of teeth. Trapped animals were then fitted with VHF radio-transmitter loop collars (Televilt, SE. weight: 50 g; frequency: 150,000–151,999 MHz) and released once deemed to be fully alert. Individuals were tracked according to scheduled monitoring of four 6-h periods (00–06; 06–12; 12–18; 18–24) per month, in order to sample a whole 24-h period per month. Within each 6-h period monitored, fixes were recorded every 30 min, field conditions permitting (e.g. adverse weather, orography, speed of radio-tagged individuals, viable paths for operators, etc.). Further fixes were also collected opportunistically. Overall, across the study areas, a total of 8950 fixes were taken, 1233 of which (13.7%) were randomly recorded. Spatial triangulation was undertaken by means of the Best Biangulation method in LOAS 3.0.1 (Ecological Software Solution 2004). Sunrise and sunset times on each monitoring day in each study area were calculated by means of the equations reported by Teets (2003).

The home-range size (hrs) of each individual was estimated for each year, with each year being broken down into the reproductive season (mating=winter vs. sexual rest=all other seasons together) and daylight phases (diurnal vs. nocturnal). Consequently, four home-range sizes per year were attributed to each individual (mating diurnal/mating nocturnal/sexual rest diurnal/sexual rest nocturnal), the year being split into four individualseasons.periods . Thus, the response variable [log(hrs), see below] used in modelling represented the same ecological unit (i.e. only fixes collected during a given reproductive period and nocturnal/diurnal period constituted the input for the home-range estimation). Home-range size estimates were further associated with the number of fixes per individualseason.period in order to account for this potentially confounding factor in data modelling. We also calculated yearly (over all seasons and periods) and seasonal (spring, summer, autumn, winter over all periods) within-year (over all periods) home-range sizes in order to provide a baseline reference for comparison with other studies.

Wildcat home-range size was calculated by means of the Brownian Bridge Movement Model (BBMM) provided in the R (version 3.0.2, R Development Core Team 2014) package “BBMM” (Nielson, R. M., Sawyer H. and McDonald T. L., unpublished). This approach jointly uses the locations and the time spent in an area to estimate the home-range size of an animal (Horne et al. 2007) and is particularly useful when dealing with locations recorded during short time-intervals, such as those considered in the present study (Horne et al. 2007, Kranstauber et al. 2012). Field trials (n=42) were conducted in both study areas to quantify the location error associated with recorded fixes; this value was required in order to calculate the BBMM home-range appropriately. According to these trials, the mean error associated with locations was 97±18 m; hence, the grid-cell size (required for BBMM calculation) was set at 200 m (approximately twice the location error).

Statistical analyses

We implemented a general additive mixed model (GAMM) fitted with restricted maximum likelihood estimation (REML, Zuur et al. 2009) and used the R package “mgcv” (Wood S., unpublished) to investigate the variation in individualseason.period home-range size. Specifically, we built the “saturated model” (a model including all potential explanatory variables) which was fitted to the data as follows: (1) the variable “individuals” was used as a random effect; (2) year was used as a random effect with a hierarchical structure within individuals, as we had no biological hypothesis about its effect; (3) the number of fixes (nfixes) per individualseason.period , which might affect the home-range size estimation, was smoothed in order to allow a potential non-linear relationship between the home-range size and the number of fixes; (4) study area (area, MRP/PPE), gender (gender, male/female), reproductive season (repro, mating/sexual rest), age-classes (age, juvenile/sub-adult/adult) and light/dark period (period, diurnal/nocturnal) were used as fixed effects; (5) additionally, on the basis of biological reasoning and previous data exploration, the following interaction terms were included as fixed effects, and model fine tuning specifications were employed as follows: (i) gender*age, to take into account the differential effect of age on the spatial behaviour of each gender; (ii) repro*gender, to take into account the differential effect of the reproductive season on the spatial behaviour of each gender; (6) home-range size (hrs) was log-transformed; (7) a Gaussian family distribution and the identity link function were employed because the response variable is normal (Zuur et al. 2010).

We then selected for the more parsimonious (sensu “best”) model among the set of candidate models using AICc. The starting model for AICc model selection was thus:


where β0 is the intercept, bi the random intercept, εi the residual for the ith individualseason.period and ϝ the smoothing function for the number of fixes and with ε ~N(0, б2) and bi ~N(0, б2). From this starting model, we selected the most parsimonious model by using the dredge function from the R package “MuMIn” (Barton 2013). All results are reported as mean±standard error unless stated otherwise.


Trapping and radio-tracking

Overall, 1516 trap-days (trapping rate=1 wildcat/379 days) were performed in the MRP, and four wildcats (morphological identifications were confirmed by genetic identification) were caught: three males and one female. All were tracked for an average of 253±56 days, with 134±14 fixes over a period of 904±318 days (Tables 1 and 2). In the PPE, 11 wildcats (9 males and 2 females) were captured over a total of 3352 trap-days (trapping rate=1 wildcat/304 days). Owing to the immaturity and/or the poor physical condition of some individuals, however, only seven individuals (6 males and 1 female) in the PPE were fitted with radio-collars. Wildcats in the PPE were tracked for an average of 128±50 days, with 44.8±4 fixes over a period of 1017±236 days (Tables 1 and 2). Overall, from 11 wildcats we obtained 85 estimations for the time periods considered.

Table 1:

BBMM home-ranges (in km2) of wildcat in Italy according to each time period.

Table 2:

BBMM home-ranges (in km2) of wildcat in Italy for each year and season.

The home range of adult male wildcats was 22.74±4.79 km2 and 6.53±0.66 km2 in the MRP and PPE, respectively. The adult female wildcat (F1) in the MRP displayed a home range of 6.17±4.71 km2, whereas the sub-adult female wildcat (F2_G) in the PPE had a home range of 4.78 km2. The home range of sub-adult male wildcats was 16.62±1.66 km2 and 6±1.84 km2 in the MRP and PPE, respectively. The home ranges of juveniles (both in the PPE) was 3.03 km2 for a male (M7_G) and 1.66 km2 for a female (F2_G) (Tables 1 and 2).

Model selection to determine home-range size

The model including study area, sex, age and interaction gender*age was best supported by the data (AICc<2, Table 3 and Supplemental Table 1). Reproductive season (repro), period (period) and the smoothing function for the number of fixes ϝ (nfixes) (d.f.=1.164, F=2.443, p=0.115) were not significant, whereas study area (area), gender (sex) and the interaction term sex*age were significant (Table 3). The results indicate that home ranges of wildcats in the MRP were larger than those in the PPE (β=1.6203±0.45, t=3.539, p<0.001) (Figure 2, Table 4). In addition, there was a significant interaction between gender and age, with males exploiting larger home ranges than females, with the notable exception of the sub-adult class in both populations (Figure 2, Table 4).

Table 3:

AICc model selection (top five models only and the null model) starting from the model log(hrsi )=β0+areai +periodi +ϝ(nfixesi )+ genderi *agei +reproi *genderi .

Wildcat home-range size predicted by gender, age-class and study site from the “best” GAMM model. nfixes was set at the median value (n=55) recorded for the dataset and y-axis are on a different scale.
Figure 2:

Wildcat home-range size predicted by gender, age-class and study site from the “best” GAMM model.

nfixes was set at the median value (n=55) recorded for the dataset and y-axis are on a different scale.

Table 4:

Estimates and significance of the variables included in the GAMM model.


Our study was the first extensive research carried out in Italy on the home-range size of the European wildcat. Collated data came from two ecologically distinct areas in which a difference in population density can be reasonably hypothesised as suggested by higher trapping rates and number of wild cats trapped per area in PPE. Furthermore, the small wildcat population in the MRP was the result of reintroduction, whereas the PPE population fell well within the historical wildcat distribution. Nevertheless, our study areas are also characterised by different management regimes, the MRP being a national park for tourism, while the PPE is a private game estate for hunting.

Pattern of variation of home-range size in Italy

Our results suggest that light conditions (night/day) and the reproductive season (mating/sexual rest) did not influence home-range sizes. The majority of felid species usually exhibit clear nocturnal activity patterns (Di Bitetti et al. 2006, Lucherini et al. 2009, Harmsen et al. 2010, Cheyne et al. 2013). Specifically, both Daniels et al. (2001) and Germain et al. (2008) found that wildcats were more active during the night.

Contrary to our expectations and despite the above mentioned difference in the activity rhythm between diurnal and nocturnal periods, we didn’t find marked differences in home-range sizes between night/day periods. This finding might suggest that the spatial distribution of resting sites overlaps the entire home range over a given season.

The relative stability of the estimated home-range sizes between the reproductive period and the sexual rest period has been observed in other studies (Stahl et al. 1998, Daniels et al. 2001, Germain et al. 2008). However, it is worth noting that a decrease in home-range sizes during the spring period has been previously reported among female wildcats (Sarmento et al. 2006), though Corbett (1979) found contrasting results. This concurs with the annual birthing period (Ragni 1981, Sarmento et al. 2006), as female wildcats involved in parental activities reduce their movements. In the present study, however, this expected phenomenon was not encountered, probably owing to the low number and relative proportion of females in our sample.

The home ranges of wildcats in the MRP were larger than those in the PPE. Wildcats in the PPE are part of the Apennine mountain wildcat population (hence a “long-term” resident population), while MRP wildcats are the descendants of a nucleus reintroduced prior to initiation of the telemetry study. Accordingly, it may be argued that the potential difference in population density (as suggested by higher trapping rates and number of wild cats trapped in PPE) could markedly affect spatial behaviour, as previously reported among populations of both lynx (Lynx lynx) and bobcat (Lynx rufus) (Benson et al. 2006, Pesenti and Zimmermann 2013). Similarly, Soto and Palomares (2013) found very large wildcat home ranges (~24 km2) within an area of low population density. However, various controlling or explanatory factors cannot be excluded; for example environmental variables such as vegetation and altitude or different habitat management regimes (e.g. potential disturbance due to hunting or tourism in our two areas) (Piñeiro et al. 2012) may also have determined the difference between home-range sizes within the two study areas.

Nevertheless, also a difference in prey densities between the study areas may have contribute in producing larger home-range in MRP; indeed it is a common finding that, when prey density is lower, home-range estimations are larger (Litvaitis et al. 1986, Avenant and Nel 1998, Herfindal et al. 2005).

Adult male wildcats displayed larger home ranges than adult females. This is in agreement with previous findings on wildcats (Daniels et al. 2001, Birò et al. 2004, Germain et al. 2008, Monterroso et al. 2009) and, more generally, on solitary and territorial carnivores. Indeed, adult males patrol large territories, which may overlap extensively with those of several females, and only slightly with those of other males (Daniels et al. 2001). This inter-sexual difference was also observed in juveniles, whose home-range sizes were similar to those of adults of the same sex. More surprisingly, in both populations, sub-adult females exhibited home-range sizes that were typical of males, albeit more variable. This pattern has never been reported before, and might be underpinned by the necessity to explore the surrounding habitat in order to find a “free” home-range for their first gestation and parturition. Further studies are required in order to understand whether this pattern should be regarded as a dispersal movement (i.e. emigration) or rather an active search for dens within the animal’s own home-range.

Comparison with other studies in Europe

Wildcat home ranges have been shown to vary widely across Europe, ranging from 1.95 to 50.17 km2 for males and 0.69–13.85 km2 for females (Monterroso et al. 2009). However, as these figures are associated with different study methodologies, local features (prey abundance) and animal ages, direct comparison is very difficult. Assuming that home ranges in the PPE are the most representative of a “stable” wildcat population (i.e. long-term population), we can observe that our yearly home-range estimates for adult male wildcats (6.53±0.66 km2) were similar to those reported by Daniels et al. (2001) in Scotland for adult tabby wildcats (4.59 km2), by Germain et al. (2008) (4.04 km2) in France and by Birò et al. (2004) (6.88 km2) in Hungary, though they were considerably smaller than that calculated by Monterroso et al. (2009) for a male wildcat (13.71 km2) in southern Portugal.

Conversely, the mean yearly home range of male wildcats in the MRP (22.74±4.78 km2) was similar to that observed by Soto and Palomares (2013) (~24 km2) and larger than that reported by Wittmer (2001) (16.62 km2); indeed, our estimates were very similar to the largest home-range size reported by Wittmer (25.15 km2).

The mean yearly home-range size of the adult female tracked in the MRP was 6.17±4.71 km2; this was larger than the values reported in most previous studies, including that of Daniels et al. (2001) (1.77 km2), Sarmento et al. (2006) (2.89 km2), Germain et al. (2008) (1.63 km2) and Monterroso et al. (2009) (2.28 km2). However, it closely matched the female home ranges observed by Birò et al. (2004) (6.24 km2).

The annual home range of the other radio-tracked female (PPE), which was a yearling at the time of capture, increased (from 1.66 to 4.78 km2) during the second year, when the sub-adult age-class was reached. Consequently, the sub-adult age effect (i.e. large home range in sub-adult females, see above), was noted within the same individual, which was monitored over the years.

Whether the variability of population density across study sites and countries is related to variability in home-range sizes on the pan-European scale remains to be investigated.

Conclusion and perspectives

The present study was the first to document the effect of population, sex and age on the home-range size of wildcats in Italy, which currently hosts four distinct populations of European wildcat (Mattucci et al. 2013), all of which are threatened with extinction. As Italian populations are among the least genetically admixed throughout their range (Randi et al. 2001, Pierpaoli et al. 2003, Lecis et al. 2006, Oliveira et al. 2008b; Mattucci et al. 2013, Anile et al. 2014), they constitute a true genotypic stronghold of wildcats in Europe. The present study fills a gap in our knowledge on a key aspect of the ecology of the wildcat in Italy. Nevertheless, further radio-telemetry research across different study areas in Italy is needed in order to describe the spatial behaviour of other Italian wildcat populations. Radio-tracking studies are difficult and expensive, hence collaboration between wildcat researchers and the authorities is necessary to effectively promote the long-term survival of this small feline in Italy.


We thank Paul Dylan Hynds and Bernard Patrick for kindly reviewing the English of the manuscript. We also thank the owner of the Paradiso di Piancino private estate, Antonio Bachetoni, the keeper, Bernardino Ciamarra, the former Director of the Maremma Regional Park, Ilio Boschi, all those who collaborated with us in collecting the data in the study areas: Lamberto Bizzarri, Simone Calandri, Paolo Capelletti, Christian Chioso, Domenico Cristofari, Marina Gigante, Andrea Mandrici, Matteo Mariani, Roberta Mazzei, Mariagrazia Possenti, Alberto Sangiuliano, Maria Tiziana Serangeli, Francesca Vercillo, Marco Catello.


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Supplemental Material:

The online version of this article (DOI: https://doi.org/10.1515/mammalia-2016-0045) offers supplementary material.

About the article

Received: 2016-04-10

Accepted: 2017-01-17

Published Online: 2017-03-02

Published in Print: 2017-12-20

Citation Information: Mammalia, Volume 82, Issue 1, Pages 1–11, ISSN (Online) 1864-1547, ISSN (Print) 0025-1461, DOI: https://doi.org/10.1515/mammalia-2016-0045.

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