Introduction

The weasel Mustela nivalis Linnaeus, 1766 is

a species with distinctive morphological and

physiological features (small size, elongated

body shape, high matabolic rate). Since it is the

smallest sized member of the order Carnivora,

this mustelid is a very specialized predator of

small rodents within their burrows, but it falls

within the prey size range of many predators.

Many behavioural traits are related to its small

size, including space use and habitat selection.

As Klemola et al. (1999) suggested, small mus-

telids choose their habitats mainly according to

prey abundance, but the risk of predation may

also modify the spacing pattern of the weasel.

The relationship between spacing pattern and

prey abundance in mustelids was also compre-

hensively described by Erlinge (1974, 1977), King

(1975), Debrot and Mermod (1983), Jêdrzejewski

et al. (1995), Macdonald et al. (2004) and Brandt

[137]

Acta Theriologica 54 (2): 137–146, 2009.

PL ISSN 0001–7051

Weasel Mustela nivalis spatial ranging behaviour and habitat

selection in agricultural landscape

Caterina MAGRINI, Emiliano MANZO, Livia ZAPPONI, Francesco M. ANGELICI,

Luigi BOITANI and Michele CENTO

Magrini C., Manzo E., Zapponi L., Angelici F. M., Boitani L. and Cento M.2009. Weasel Mustela nivalis spatial ranging behaviour and habitat selectionin agricultural landscape. Acta Theriologica 54: 137–146.

This paper reports the findings of a study on the spacing pattern of a popu-lation of weasels Mustela nivalis Linnaeus, 1758 in central Italy. We describethis pattern at spatial and habitat level, meant as a set of vegetational andenvironmental features. The study area is a typical agricultural landscape,consisting of highly fragmented natural habitat modified by thousands ofyears of human presence and work. The results indicate that individual homeranges vary greatly from non breeding to breeding season: during spring andsummer, weasels increase their movements and the number of tracts theycross, which results in home range areas up to 10 times larger. Moreover thisstudy demonstrates a strong preference of weasels for habitats formed bynatural residual edges between fields and meadows. The shapes of theindividual home ranges follow these edges, producing a typical linear spatialhome range pattern.

Dipartimento di Scienze Ambientali, Universit� di Parma, Italy, e-mail: caterina.magrini@ethoikos.it(CM); Dipartimento di Biologia Animale e dell’Uomo , Universit� La Sapienza, Roma, Italy (EM,LZ, LB, MC), Fondazione Italiana Zoologia dei Vertebrati, Roma, Italy (FMA)

Key words: Mustelid, small carnivore, home range, spacing behaviour

and Lambin (2007), Zub et al. (2008), while the

association between spacing pattern and preda-

tion risk was studied in weasel by King and

Moors (1979), Erlinge and Sandell (1988), Kor-

pimäki and Norrdahl (1989) and Brandt and

Lambin (2007), Zub et al. (2008). Trophic spe-

cialization seems to have an influence on the

choice of suitable habitat for this species: agri-

cultural landscapes yield high densities of prey

populations as well as residual high covered

habitat to escape from predators (Simms 1979,

Klemola et al. 1999).

In this paper, we use the term ‘home range’,

as defined by King (1975), which covers the en-

tire spectrum between a defended area with

clear-cut boundaries and a system with freely

overlapping movements. Although many au-

thors in the past have described mustelid spac-

ing pattern as actual territorial behaviour, with

active defence and prevention of settlement by

neighbours (Lockie 1966, Erlinge 1974, 1977),

we prefer the use of the home range concept, be-

cause it is a general concept that may or may not

include territorial behaviour. Powell (1979) also

defined intra-sexual territorialism for the genus

Mustela, but suggested that this spacing pattern

may change locally in relation to food density,

habitat availability, and sexual activity. Sandell

(1989) summarized the spacing pattern of soli-

tary carnivores, showing that the main factor in-

fluencing the shift between territorial and non

territorial behaviour was resource distribution,

specifically food supply and mating partners.

The aim of this study was to illustrate some

features of weasel ecology, particularly those

concerning the spacing pattern, analysed in a

landscape highly fragmented by human activity.

Study area

The research was conducted in the Regional Natural

Reserve of Lungo and Ripasottile Lakes, in the province of

Rieti, central Italy. The area is typical intra-montane ba-

sin, closed on the north-east by the Reatini Mountains

(highest peak Terminillo, 2216 m), and on the south-west

by the Sabini Mountains (highest peak Tancia, 1282 m).

The Reserve occupies an area of 3278 ha of agricultural

landscape.

The local plant cover was made up of strips of mixed

copse woodland, mainly represented by oaks Quercus sp.,

ashes Fraxinus sp., hornbeams Carpinus sp., and black-

-thorns Prunus sp., and riparian vegetation mainly com-

posed by willows Salix sp., poplars Populus sp. and elder

Sambucus sp., interspersed with intensive cultivations, like

oat Avena sativa, wheat Triticum sativum, corn Zea mays,

sugar beet Beta vulgaris crassa and sunflower Helianthus

annuus.

Material and methods

Trapping and radio tracking

Field data collection was carried out from February

2003 to May 2004. Weasels were trapped using Edgar

wooden box traps (King and Edgar 1977). The Edgar live

traps used in this research were 60 cm long, 12 cm wide and

15 cm high, hand made from 1 cm thick wood, treated with

mordant varnish.

Trapping sessions were conducted every month for dif-

ferent periods of time and the trapping effort was variable

by year and season, based on the number of radio tracked

animals in a sampling period. Twenty to 50 traps worked si-

multaneously during the data collection period, the number

of traps was so variable because, during the same period,

some traps were taken for maintenance, and some were sto-

len. The traps were placed throughout a study area of 900

ha. Trap sites were chosen in the most suitable habitats

(stone walls, ditches and hedgerows), at variable distance

from each other, usually from 20 to 50 m. During data col-

lection traps were moved over different locations inside

study area, in order to capture different animals. The traps

were baited with dead house mice Mus domesticus and

checked twice a day, once in the morning and subsequently

12 hours later. During the cold season, from November to

March, the traps were disarmed at night.

Captured animals were transferred from the trap to a

sealed transparent plastic box, used as a pre-anaesthetisation

chamber, in which cotton wetted with ethyl ether was intro-

duced. Each animal was weighed to evaluate the exact dose

of anaesthetic and intramuscularly injected with ketamine.

Anaesthesia lasted an average of 10 minutes per animal.

Each captured animal was marked with an individually

numbered transponder tag (Trovan, UK), inserted subcuta-

neously between the shoulder blades. Each animals was

also fitted with a radio transmitter, equipped with an exter-

nal PIP model antenna (Biotrack, UK; 7 cm, 1 g). The

weight of the radio tag represented approximately 1% of an

adult females’ body weight and 0,5% of an adult males’ body

weight. The tags were fitted to the animals by a thin satin

collar, sewn on with cotton. After handling them, the ani-

mals were kept in a cage for the following 12 hours and

were fed, in order to monitor their health and the possible

reactions to anaesthetic. All tagged animals (which did not

lose the collars) were recaptured and the collars were re-

moved from their necks, when the transmitters were broken

or the batteries ran out.

Seventeen weasels were captured (14 males and 3 fe-

males), of which 9 (53%) were recaptured several times, for

138 C. Magrini et al.

a total of 46 captures. The total number of radio locations

was 1846, from 14 animals, but only 6 adult animals were

followed over enough days for spatial analysis. From 14

tagged animals, 6 of them lost the collars few days after re-

lease.

Although the battery life of transmitters averaged about

30–40 days, many radio tags were lost or broken within an

average of 10 days after being fitted. The range of their sig-

nal varies from 20 to 200 m, depending on the vegetation

and ground features of area occupied by the animal, and its

underground movements. A radio receiver (Custom, USA)

with a directional handle antenna was used to locate the

animals.

Animal locations were taken by homing methodology, a

simple, non triangulation technique that enables the real

position of the tracked animal to be estimated by following

the signal’s increasing strength (White and Garrott 1990).

There was no error associated with this methodology be-

cause animal location was concretely taken and not simply

estimated. The only error was introduced by the quality of

the map. A 1:10 000 map of the study area was used, and

the individual positions were taken in kilometric coordi-

nates UTM, so the error introduced by this mapping system

was 10 m.

Activity state was determined by the presence of inter-

mittent signal from tags. In order to maximize the amount

of data collected during the short time the radio tags were

working, the sampling strategy consisted in taking animal

locations every 15 minutes, for 8 hours continuously, fol-

lowed by 8 hours of rest, round the clock (Naef-Daenzer

1993, Jêdrzejewski et al. 1995, Samson and Raymond 1998).

For small mammals, the constraints of short battery life

mean that continuous tracking is the only option, since lon-

ger time intervals would yield too few location fixes (Harris

et al. 1990).

Data analysis

For home range analysis we used continuous locations.

Eliminating auto correlated data by sub-sampling reduces

both the accuracy and precision of the estimates (De Solla et

al. 1999) and limits the biological significance of the analy-

sis, because animal behaviour is essentially a dependent

phenomenon, and statistical independence is often not the

same as biological independence (Lair 1987, Rooney et al.

1998). The time period over which a home range is mea-

sured is one of the most important parameters needed to

fully define the home range (Morris 1988). For the home

range analysis, the sample period was selected to obtain an

equal number of fixes over the same temporal frame for

each individual. In particular, a normalized sample of 100

fixes per animal was used, referred to 5 continuous days,

not including data from first day after the release. This pro-

cedure was possible because of the homogeneous distribu-

tion of locations throughout the 24 hours of the day for

every weasel.

In this study, radio tracking data refer to small tempo-

ral frames. We analysed them both with non statistical

methods, the minimum convex polygon (MCP) (Mohr 1947)

and the grid cells count (GCC) (Siniff and Tester 1965) and

with a statistical non parametric method, the Kernel esti-

mator (Worton 1989). For GCC, we chose a cell size of 10 �

10 m, corresponding to the error associated to animal loca-

tions in this study, and assumed that cells crossed by the

straight line joining two consecutive locations should also

be counted as part of the home range area, as suggested by

White and Garrott (1990). Among the possible non paramet-

ric methods, we chose the fixed kernel estimator with the

least square cross validation (LSCV) smoothing parameter

(Worton 1995, Seaman and Powell 1996, Seaman et al.

1999). Home range analyses were done using Animal Move-

ment, version 2.0 (Alaska Biological Science Center).

Habitat selection is defined in terms of differential use

of available habitat types (Garshelis 2000). In this study

the term selection was described as the ‘second order selec-

tion’ of a population inside an area (Johnson 1980). John-

son’s methodology was used to perform statistical analysis.

So the animals and not the locations were the sampling

units and it was possible to determine habitat selection

without an exact assessment of habitat availability. There-

fore availability was determined by the polygon approach,

in which the sum of the areas of the polygons of each habi-

tat type provided the total area of each habitat type (White

and Garrott 1990). The MCP estimates of individual home

ranges were used, because they represent a descriptive defi-

nition of home ranges, not including the use of UD (utiliza-

tion distribution) area. In fact, the UD itself produces a

probability of use of a particular resource inside the individ-

ual range (Marzluff et al. 2001), and it is not the best home

range descriptor to be used in the availability analysis.

Three habitat types were chosen, and their relative avail-

ability was determined within the individual home range

areas.

The three habitat types were:

A. cultivated fields and meadows,

B. human settlements including houses, haylofts, sta-

bles, henhouses, industrial structures, paved or unpaved

roads accessible to cars,

C. corridors of natural environment represented by

woodland and hedges, including all spaces between fields,

between fields and rivers, streams or waterways, and be-

tween fields and roads, often represented by small channels.

The pattern of use was defined as the number of loca-

tions recorded within each habitat type. The use of homing

methodology reduced the risk of biased telemetry data on

habitat use (Garshelis 2000).

Habitat analyses were performed using Prefer, version

5.1 (Northern Praire Science Center) and Arcview, version

3.3 (Environmental Systems Research Institute, Inc).

Results

Estimates of home range size varied greatly

between individuals (Table 1), because of sea-

sonal changes in spacing behaviour. Based on

100 fixes per animal, the average area estimated

by the GCC method represents only 4,6% of the

average area estimated by the MCP methodol-

Space use in weasels 139

ogy, and the average area estimated with the

Kernel 50% represents only 26,8% of the aver-

age area estimated by Kernel 95% methodology.

The reason for these discrepancies is that the

MCP and Kernel 95% estimates included large

open areas never crossed by the animals, whereas

the GCC or the Kernel 50% better represented

linear features across non-suitable habitats.

When the results were broken down, only for

males, into two half-year periods, spring/sum-

mer (n = 3) and autumn/winter (n = 2), there was

a variation in the seasonal means (U(2, 3) = 0,

p < 0.1). There was a reduction of mean home

range area by 90.7% (using MCP estimator),

75.7% (using GCC estimator), 94.5% (using Ker-

nel 95% estimator) and 94.1% (using Kernel 50%

estimator) from the spring/summer season to

autumn/winter season (Table 2).

The relative availability of the three pre-de-

fined habitat types within the individual home

ranges (estimated by MCP 100%) and their indi-

vidual use was shown in Table 3.

The weasels did not use the habitat types in

proportion to their availability (F(2,4) = 106, p <

0.05). The most strongly preferred habitats were

residual natural environment represented by

woodland and hedges, including corridors be-

tween fields, between fields and rivers, streams

140 C. Magrini et al.

Table 1. Home range size of the weasels calculated with different estimators. MCP – min-

imum convex polygon, GCC – grid cells count, M – male, F – female. Number of locations

was 100 for each weasel.

Weasel Radio-tracking sessionMCP 100%

(ha)GCC (ha)

Kernel 95%

(ha)

Kernel 50%

(ha)

M1 25/02 to 01/03 2003 9 0.8 1.9 0.2

M2 15/05 to 19/05 2003 44 2.4 50.4 4.2

M3 04/07 to 08/07 2003 90 3.2 80.5 6.4

M4 17/09 to 21/09 2003 114 4.4 68.2 9.8

M5 24/10 to 28/10 2003 10 0.9 5.1 0.7

F1 14/02 to 18/02 2004 4 0.9 3.9 0.5

Mean 45 2.1 35 9.4

SD 46.8 1.6 35.6 7.4

Table 2. Seasonal variation in weasel home range size mean and in standard deviation

(n = 5).

HR estimator SeasonHome range size (ha)

Seasonal %

variationMean SD

MCP 100% spring/summer 82.6 35.5 90.7

autumn/winter 7.6 3.2

GCC spring/summer 3.3 1 75.7

autumn/winter 0.8 0.1

Kernel 95% spring/summer 66.3 15.1 94.5

autumn/winter 3.6 1.6

Kernel 50% spring/summer 6.8 2.1 94.1

autumn/winter 0.4 0.2

or waterways, and between fields and roads, of-

ten represented by small channels, followed by

human infrastructures (Table 4). Multiple com-

parisons (W = 3.01, K = 100) (Waller and Duncan

1969) showed that natural residual edge habi-

tats were preferred over cultivated fields (abso-

lute standard difference in mean rank = 16.1),

and also that human settlements including

houses, haylofts, stables, henhouses, industrial

structures, paved or unpaved roads accessible to

cars were preferred over cultivated fields (abso-

lute standard difference in mean rank = 3.87)

even though this latter habitat type was the

most widely available in the study area.

Moreover, the weasels were active during

38% of locations in natural residual edges and

during 29% of locations in human infrastruc-

tures, showing their activity pattern was simi-

lar within the two preferred habitats (�2= 3.1,

p > 0.05).

Discussion

Because of the semifossorial behaviour of

weasels, there was more stress on the collars

leading to breakage and loss. Therefore we gath-

ered less data than radio tracking studies on

larger mammals. Non statistical methodologies

are useful when extremely small data sets are

available: we used both MCP to provide simple

and comparable estimates, and GCC, which is

able to describe the internal structure of the

home range and provide an estimation of its size

and shape allowing for better interpretation of

biological activity. Macdonald et al. (2004) sug-

gested that the use of linear strip (LS) home

range estimation methodology, the linearity of

the most preferred habitat type (edges) confirms

the biological accuracy of the home range shape

and size documented by non statistical and de-

scriptive method (in this study by GCC), and

Space use in weasels 141

Table 3. Individual habitat availability and use inside weasel home ranges. n – number of locations.

Weasel n

MCP

100%

(ha)

Habitat types

Cultivated fields and

meadowsHuman settlements

Corridors of natural

environment

Availability

(%)

Use

(%)

Availability

(%)

Use

(%)

Availability

(%)

Use

(%)

M1 118 10 85.8 0.8 3 0 11.1 99.1

M2 126 44 96 0.7 1.6 0 2.2 99.2

M3 219 89.7 92.3 0.4 3 3.6 4.6 95.8

M4 297 160.2 86.2 0 4.1 37.7 9.5 60.6

M5 247 54.6 88.3 0 7.2 82.1 4.4 11.7

F1 276 12.8 80.7 0.3 0.5 0.3 18.7 99.2

Table 4. Ranking of habitat types from most preferred to

least preferred by weasels and average difference in rank

(d) for each habitat type.

Habitat type Rank d

Corridors of natural environment 1 –1.16

Human settlements 2 –0.41

Cultivated fields and meadows 3 1.58

supports the idea formulated by Grant et al.

(1992) that habitat selection can be an impor-

tant index of space use.

Home range size and spacing patterns

Quantitative weasel home range size data

from the literature have been obtained from few

studies by radio tracking: Pounds (1981) found

an average winter value of 34 ha for males and

25 ha for females, Jêdrzejewski et al. (1995) found

an average male autumn/winter home range of

17.5 ha and an average male spring/summer one

of 100 ha, and Macdonald et al. (2004) an average

male home range of 48.8 ha in autumn/winter

and of 82 ha in spring/summer and an average

female home range of 29.2 ha in autumn and

16.2 ha in summer. The results from our study

are very close to those in Jêdrzejewski et al.

(1995) and in Macdonald et al. (2004), which

were obtained with the same method of collec-

tion (radio tracking) and analysis (MCP 100%),

while data from Pounds (1981) are difficult to

compare as they referred to winter season only.

Moors (1974), Pounds (1981) and Macdonald

et al. (2004) reported a linear shape of weasels’

home ranges in farmland environment, whereas

Jêdrzejewski et al. (1995) described circular

home ranges in deciduous forest landscape. But

all these authors showed that the area actually

utilized by the animals was only 4 to 24% of the

total home range. McDonald and Harris (1998)

also showed that, when home range size was cal-

culated by measuring the area of a corridor of 10

m around edges, thereby excluding the unpro-

ductive centres of fields, weasel ranges on farm-

land were less than 10 ha. Only one published

study (Macdonald et al. 2004) used radio track-

ing to reveal the linear shape of weasel home

ranges, so the results of our research are impor-

tant to confirm this finding, showing that the

area actually used by individuals inside a home

range area enclosed by MCP has a linear shape

and amounts to only 5% of the total estimated

home range.

The spacing pattern observed in a given

population is the consequence of the tactics

chosen by the individual animals in their at-

tempts to survive and maximize reproductive

fitness. Regardless of the influence of seasonal

availability and distribution of food, in many

solitary polygynous-promiscuous mammals, in-

dividual movements are seasonally influenced

by reproductive activity (Bekoff et al. 1984,

Sandell 1989).

In agreement with this, we documented a re-

markable expansion in home range sizes from

the non breeding to the breeding season, due

to the increase of individuals’ movements in

searching for partners to mate (Brandt and

Lambin 2007), and to the regular seasonal reor-

ganization of the home ranges after the appear-

ance of the new crop of juveniles (Moors 1974,

Macdonald et al. 2004, King 2007).

Habitat selection

Habitat use data have been gathered only for

a small number of species in the family Muste-

lidae, and consequently the knowledge of the

landscape ecology of this family is very limited

(Gough and Rushton 2000).

Data from this study provide evidence of a

positive selection for hedges in agricultural

landscape. The weasels’ preference for linear

habitats mainly composed of stone walls, fence

lines around fields, riparian habitats and edge

vegetation in farmland environment has been

reported by trappers and researchers for many

years (Polder 1968, Moors 1974, Pounds 1981,

Boria and Prigioni 1993, Sheffield and King

1994, McDonald and Harris 1998, Angelici 2003,

King 2007), but only few studies (Pounds 1981,

Macdonald et al. 2004, Brandt and Lambin

2007) documented this point by radio tracking.

Some studies on the stoat Mustela erminea have

shown the same habitat preference, in particu-

lar for early successional vegetation communi-

ties, plus an actual avoidance for forested

habitats (Vaisfeld 1972, Erlinge 1977, Simms

1979, Debrot and Mermod 1983, Murphy and

Dowding 1994, Samson and Raymond 1998,

King 2007). Also Gehring and Swihart (2004)

reached the same conclusion about long tailed

weasel Mustela frenata in Indiana (USA).

Although agriculture is one of the main

causes of natural habitat loss and degradation

(Groom and Vynne 2006), European farm land-

142 C. Magrini et al.

scapes are systems where human activities

repeatedly create disturbances (endogenous)

through evolutionary time (Angelstam 1992, Ko-

zakiewicz et al. 1999), upon which the elements

of biological diversity depend (McIntyre and

Hobbs 1999, McNeely and Scherr 2006). The

basic condition for the use of agricultural land-

scape by the animal community is the presence

of residual natural habitats used as corridors

through the matrix (Middleton and Merriam

1983, Saunders et al. 1991).

The general view is that small mustelids

prefer farmland habitats rather than woodland

habitats (Klemola et al. 1999, Zub et al. 2008).

As a matter of fact, fragmented farm landscape

crossed by residual edge habitat favours meso-

predator release (Crooks and Soulè 1999); these

middle sized species can better exploit linear

edge habitats (Palomares and Caro 1999, Crooks

2002, Gehring and Swihart 2003).

Two main reasons account for the habitat

preference of weasels in a rural environment:

cover and food requirements. Weber (1988) de-

scribes an enclosure experiment on the micro-

habitat preference of polecats Mustela putorius,

a species which lives in environments similar to

those occupied by the weasel. Weber reported a

preference for densely structured habitats, like

edge vegetation, and proposed that the reason

has more to do with the cover providing refuge

from larger predators than with the availability

of prey. The same conclusion was inferred by a

study on drainage culverts in the agricultural

environment (Clevenger et al. 2001); culverts

were mainly used by weasels and selection for

this habitat was linked to the structural fea-

tures of the culverts (cover, depth), more than

prey abundance. Moreover, Brandt and Lambin

(2007) considered that selection of high grass

cover by weasels might reflect the avoidance for

habitat with high intraguild predation risk. Also

Zub et al. (2008) suggested that, at local scale,

availability of dense plant cover and other habi-

tat requirements, instead of the abundance of

prey, was the most important factor affecting

weasel habitat selection, in complex ecosystems

of the temperate zone.

However, the distribution of prey may be

another reason for this preference. Although

hedges are one of the most prey rich habitats for

weasels (Tattersall et al. 2001, 2002), middle and

small sized predators, like mustelids, also benefit

from the use of linear edge habitats because

these corridors cross more habitats, where ani-

mals can feed by spill over predation (Schneider

2001). Actually cultivated fields are used for

food and cover by many species of prey, in

particular Apodemus sp. (Tew et al. 1994, Ko-

zakiewicz et al. 1999), and Microtus sp. (Manson

et al. 1999). The weasel is a small predator, with

a specialized trophic niche: their predators in-

clude raptors, snakes, men, and larger carnivores

(Gerdol and Mantovani 1980, Korpimaki and

Norrdahl 1989, Bertarelli et al. 1992, Angelici

and Amori 1994, Angelici and Luiselli 1998,

Angelici 2003). Well vegetated habitats there-

fore give protection from predation and also

enable movements from outside the edge to

hunting areas composed of agricultural fields

and meadows, where the usual prey of weasel

live. In fact, the study area supports populations

of Savi’s pine vole Microtus savii, wood mouse

Apodemus sylvaticus and house mouse Mus do-

mesticus, the usual rodent prey species for

weasels, whose ecology is linked with fields in

the agricultural landscape (Capizzi and Santini

2002).

On the other hand, rural structures like

haylofts and henhouses are used both for provid-

ing cover and allowing predation on domestic

species (chickens and rabbits) and the house

mouse Mus domesticus, which live in higher

density near human settlements, regardless of

spill-over predation.

Lastly, this study assesses that the two pre-

ferred habitats, although quantitatively used in

a different way (natural edges were used more

than rural structures), were qualitatively used

in the same way. Actually there is evidence that

both habitats are used for the same activity

(resting, moving). However, natural edge habi-

tats are more frequently used because they are

the only spaces that enable the crossing of the

agricultural matrix.

Acknowledgements: We wish to thank the Regional NaturalReserve of Lungo and Ripasottile Lakes for allowing andsupporting our study. C. King, P. Ciucci and G. Orecchiaprovided invaluable advices.

Space use in weasels 143

References

Angelici F. M. 2003. Mustela nivalis (Linnaeus, 1766). [In:

Mammalia III: Carnivora-Artiodactyla. L. Boitani, S.

Lovari and A. Vigna Taglianti, eds]. Calderini, Bologna:

142–152.

Angelici F. M. and Amori G. 1994. [Mammals preyed on

by hawk species in Italy]. [In: Atti del VI Convegno

Italiano di Ornitologia]. Torino: 417– 418. [In Italian]

Angelici F. M. and Luiselli L. 1998. Patterns of mam-

mal-eating by snakes in Italian Alps and in peninsular

Italy: a review. Ecologia Mediterranea 24: 1–13.

Angelstam H. 1992. Conservation of communities: the im-

portance of edges, surroundings and landscape mosaic

structure. [In: Ecological principles of nature conserva-

tion; applications in temperate and boreal environ-

ments. L. Hansson, ed]. Elsevier Science Pub., London:

252– 325.

Bekoff M., Daniels T. J. and Gittleman J. L. 1984. Life

history patterns and the comparative social ecology of

carnivores. Annual Review Ecology Systematics 15:

191–232.

Bertarelli C., Gelati A. and Giannella C. 1992. [Preliminary

data on tawny owl (Strix aluco) and barn owl (Tyto alba)

winter diet in the low Modena district]. Picus 18: 133–140.

[In Italian]

Boria A. and Prigioni C. 1993. [Home range size and feeding

preference of weasel (Mustela nivalis) in cultivated area

of the Po Valley]. [In: Riassunti del II Simposio Italiano

sui Carnivori, Biologia e conservazione dei mustelidi. C.

Prigioni, ed]. Pavia. [In Italian]

Brandt M. J. and Lambin X. 2007. Movement patterns of

specialist predator, the weasel Mustela nivalis exploit-

ing asynchronous cyclic field vole Microtus agrestis pop-

ulations. Acta Theriologica 52: 13–25.

Capizzi D. and Santini L. 2002. [Savi pine vole, wood mouse,

house mouse]. [In: Mammiferi d’Italia. M. Spagnesi and

A. M. De Marinis, eds]. Ministero dell’Ambiente e della

Tutela del Territorio, Direzione Conservazione della Na-

tura, Istituto Nazionale di Fauna Selvatica Alessandro

Ghigi, Roma, Bologna: 188–189, 199–200, 203–204. [In

Italian]

Clevenger A. P., Chruszcz B. and Gunson K. 2001. Drainage

culverts as habitat linkages and factors affecting passage

by mammals. Journal Applied Ecology 38: 1340–1349.

Crooks K. R. 2002. Relative sensitivities of mammalian car-

nivores to habitat fragmentation. Conservation Biology

16: 488–502.

Crooks K. R. and Soulé M. E. 1999. Mesopredator release

and avifaunal extinctions in fragmented system. Nature

400: 563–566.

Debrot S. and Mermod C. 1983. The spatial and temporal

distribution pattern of the stoat (Mustela erminea L.).

Oecologia 59: 69–73.

De Solla S. R., Bonduriansky R. and Brooks R. J. 1999.

Eliminating auto-correlation reduces biological rele-

vance of home range estimates. Journal of Animal

Ecology 68: 221–234.

Erlinge S. 1974. Distribution, territoriality and numbers of

the weasel Mustela nivalis in relation to prey abun-

dance. Oikos 25: 308–314.

Erlinge S. 1977. Spacing strategy in stoat Mustela erminea

L. Oikos 28: 32–42.

Erlinge S. and Sandell M. 1988. Coexistence of stoat Mus-

tela erminea, and weasel Mustela nivalis: social domin-

ance, scent communication and reciprocal distribution.

Oikos 53: 242–246.

Garshelis D. L. 2000. Delusions in habitat evaluation: mea-

suring use, selection, and importance. [In: Research

techniques in animal ecology. L. Boitani and T. K.

Fuller, eds]. Columbia University Press, New York:

111–164.

Gehring T. M. and Swihart R. K. 2003. Body size, niche

breadth, and ecologically scaled responses to habitat

fragmentation: mammalian predators in an agricultural

landscape. Biological Conservation 109: 283–295.

Gehring T. M. and Swihart R. K. 2004. Home range and

movements of long-tailed weasels in a landscape frag-

mented by agriculture. Journal Mammalogy 85: 79–86.

Gerdol R. and Mantovani E. 1980. [Preliminary data on

barn owl (Tyto alba) predation in Ferrara district].

Avocetta 4: 83–86. [In Italian]

Gough M. C. and Rushton S. P. 2000. The application of

GIS-modelling to mustelid landscape ecology. Mammal

Review 30: 197–216.

Grant J. W. A., Chapman C. A. and Richardson K. S. 1992.

Defended versus undefended home range size of carni-

vores, ungulates and primates. Behavioural Ecology

Sociobiology 31: 149–161.

Groom M. J. and Vynne C. H. 2006. Habitat degradation

and loss. [In: Principles of conservation biology. M. J.

Groom, G. K. Meffe and C. R. Carroll, eds]. Sinauer As-

sociates, Suderland: 173–212.

Harris S., Cresswell W. J., Forde P. G., Trewhella W. J.,

Woollard T. and Wray S. 1990. Home range analysis us-

ing radio tracking data: a review of problems and tech-

niques particularly as applied to the study of mammals.

Mammal Review 20: 97–123.

Jêdrzejewski W., Jêdrzejewska B. and Szymura L. 1995.

Weasel population response, home range, and predation

on rodents in a deciduous forest in Poland. Ecology 76:

179–195.

Johnson D. H. 1980. The comparison of usage and availabil-

ity measurements for evaluating resource preference.

Ecology 61: 65–71.

King C. M. 1975. The home range of the weasel (Mustela

nivalis) in an English woodland. Journal of Animal

Ecology 44: 639–668.

King C. M. 2007. The natural history of weasels and stoats.

Christopher Helm (eds), London: 1–464.

King C. M. and Edgar R. L. 1977. Techniques for trapping

and tracking stoats (Mustela erminea); a review, and a

new system. New Zealand Journal of Zoology 4: 193–212.

144 C. Magrini et al.

King C. M. and Moors P. J. 1979. On coexistence, for-

aging strategy and biogeography of weasels and stoats.

Oecologia 39: 129–150.

Klemola T., Korpimaki E., Norrdahal K., Tanhuanpaa M.

and Koivula M. 1999. Mobility and habitat utilization of

small mustelids in relation to cyclically fluctuating prey

abundances. Annales Zoologici Fennici 36: 75–82.

Korpimäki E. and Norrdahl K. 1989. Avian predation on

mustelids in Europe: occurrence and effects on body size

variation and life traits. Oikos 55: 205–215.

Kozakiewicz M., Gortat T., Kozakiewicz A. and Barkowska

M. 1999. Effects of habitat fragmentation on four rodent

species in a Polish farm landscape. Landscape Ecology

14: 391–400.

Lair H. 1987. Estimating the location of the focal centre in

red squirrel home range. Ecology 68: 1092–1101.

Lockie J. D. 1966. Territory in small carnivores. Sympo-

sium of Zoological Society of London 18: 143–165.

Macdonald D. W., Tew T. E. and Todd I. A. 2004. The ecol-

ogy of weasels (Mustela nivalis) on mixed farmland in

southern England. Biologia (Bratislavia) 59: 235–241.

Manson R. H., Ostfeld R. S. and Canham C. D. 1999.

Responses of a small mammal community to hetero-

geneity along forest-old-field edges. Landscape Ecology

14: 355–367.

Marzluff J. M., Knick S. T. and Millspaugh J. J. 2001. High-

tech behavioural ecology: modelling the distribution of

animal activities. [In: Radio tracking and animal popu-

lations. J. J. Millspaugh and J. M. Marzluff, eds]. Aca-

demic Press, San Diego: 309–326.

McDonald R. A. and Harris S. 1998. Stoats and weasels.

The Mammal Society (eds), London: 1–32.

McIntyre S. and Hobbs R. 1999. A framework for conceptu-

alizing human effects on landscapes and its relevance to

management and research models. Conservation Biol-

ogy 13: 1282–1292.

McNeely J. A. and Scherr S. J. 2006. Promoting wildlife

conservation in agricultural landscapes. [In: Principles

of conservation biology. M. J. Groom, G. K. Meffe and

C. R. Carroll, eds]. Sinauer Associates, Sunderland:

208–211.

Middleton J. and Merriam G. 1983. Distribution of wood-

land species in farmland woods. Journal of Applied

Ecology 20: 625–644.

Mohr C. O. 1947. Table of equivalent populations of North

American small mammals. American Midland Natural-

ist 37: 223–249.

Moors P. J. 1974. The annual energy budget of a weasel

(Mustela nivalis) population in farmland. PhD thesis,

Aberdeen University, Aberdeen: 1–153.

Morris P. A. 1988. A study of home range and movements in

the hedgehog (Erinaceus europaeus). Journal of Zoology,

London 214: 433–449.

Murphy E. C. and Dowding J. E. 1994. Range and diet of

stoats (Mustela erminea) in a New Zealand beech forest.

New Zealand Journal of Ecology 8: 11–18.

Naef-Daenzer B. 1993. A new transmitter for small animals

and enhanced methods of home range analysis. The

Journal of Wildlife Management 57: 680–689.

Palomares F. and Caro T. M. 1999. Interspecific killing

among mammalian carnivores. The American Natural-

ist 153: 492–508.

Polder E. 1968. Spotted skunk and weasel populations den

and cover usage in northeast Iowa. Transactions of Iowa

Academy Science 75: 142–146.

Pounds C. J. 1981. Niche overlap in sympatric populations

of stoats (Mustela erminea) and weasels (Mustela niva-

lis) in northeast Scotland. PhD thesis, Aberdeen Uni-

versity, Aberdeen: 1–326.

Powell R. A. 1979. Mustelid spacing patterns: variations on

a theme by Mustela. Zeitschrift Tierpsychologie 50:

153–165.

Rooney S. M., Wolfe A. and Hayden T. J. 1998. Auto-

correlated data in telemetry studies: time to independ-

ence and the problem of behavioural effects. Mammal

Review 28: 89–98.

Samson C. and Raymond M. 1998. Movement and habitat

preference of radio tracked stoats, Mustela erminea,

during summer in southern Quebec. Mammalia 62:

165–174.

Sandell M. 1989. The mating tactics and spacing patterns of

solitary carnivores. [In: Carnivore behaviour, ecology

and evolution. J. L. Gittleman, ed]. Cornell University

Press, Ithaca: 164–182.

Saunders D. A., Hobbs R. J. and Margules C. R. 1991. Bio-

logical consequences of ecosystem fragmentation: a re-

view. Conservation Biology 5: 18–32.

Schneider M. F. 2001. Habitat loss, fragmentation and

predator impact: spatial implication for prey conserva-

tion. Journal of Applied Ecology 38: 720–735.

Seaman D. E., Millspaugh J. J., Kernohan B. J., Brundige

G. C., Raedeke K. J. and Gitzen R. A. 1999. Effects of

sample size on kernel home range estimates. The Jour-

nal of Wildlife Management 63: 739–747.

Seaman D. E. and Powell R. A. 1996. An evaluation of the

accuracy of kernel density estimators for home range

analysis. Ecology 77: 2075–2085.

Sheffield S. R. and King C. M. 1994. Mustela nivalis. Mam-

malian Species 454: 1–10.

Simms D. A. 1979. Studies on a ermine population in south-

ern Ontario. Canadian Journal of Zoology 57: 824–832.

Siniff D. B. and Tester J. R. 1965. Computer analysis of ani-

mal movement data obtained by telemetry. Bioscience

15: 104–108.

Tattersall F. H., Macdonald D. W., Hart B. J., Johnson P.

J., Manley W. J. and Feber R. E. 2002 Is habitat linear-

ity important for small mammal communities on farm-

land? Journal of Applied Ecology 39: 643–652.

Tattersall F. H., Macdonald D. W., Hart B. J., Manley W. J.

and Feber R. E. 2001. Habitat use by wood mice (Apo-

demus sylvaticus) in a changeable arable landscape.

Journal of Zoology, London 255: 487–494.

Space use in weasels 145

Tew T. E., Todd I. A. and Macdonald D. W. 1994. Field mar-

gins and small mammals. BCPC Monograph 58: 85–93.

Vaisfeld M. A. 1972. Ecology of stoat in the cold season

in the European North. Zoologicheskii Zhurnal 51:

1705–1714.

Waller R. A. and Duncan D. B. 1969 A Bayes rule for the

symmetric multiple comparisons problem. Journal of

American Statistic Association 64: 1484–1503.

Weber D. 1988. Experiments on microhabitat preference of

polecats. Acta Theriologica 33: 403–413.

White G. C. and Garrott R. A. 1990 Analysis of wildlife

radio-tracking data. Academic Press (eds), San Diego:

1–383.

Worton B. J. 1989. Kernel methods for estimating the utili-

zation distribution in home range studies. Ecology 70:

164–168.

Worton B. J. 1995. Using Monte Carlo simulation to evalu-

ate Kernel-based home range estimators. The Journal of

Wildlife Management 59: 794–800.

Zub K., Sonnichsen L. and Szafrañska P. A. 2008. Habitat

requirements of weasels Mustela nivalis constrain their

impact on prey populations in complex ecosystems of

the temperate zone. Oecologia 157: 571–582.

Received 22 July 2008, accepted 22 September 2008.

Associate editor was Karol Zub.

146 C. Magrini et al.