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Introduction

Adult ungulate species commonly use differ-

ent anti-predator strategies to avoid attacks by

predators such as birth synchrony (Estes 1966,

Adams and Dale 1998) , grouping (Ha milton

1971, Hebblewhite and Pletscher 2002), migra-

tion (Fryxell et al. 1988, Fryxell and Sinclair

1988, Nelson and Mech 1991), protective cover

(Lima and Dill 1990), escape features such as

standing in water (Mech 1966), increased vigi-

lance (Hunter and Skinner 1998, Berger 1999),

alarm vocalizations (Berger 1978) or physical

traits such as size (Mech 1966). When attacked

[207]

Acta Theriologica 54 (3): 207218, 2009.

PL ISSN 00017051 DOI: 10.4098/j.at.00017051.082.2008

Wolf predation on moose and roe deer: chase distances and

outcome of encounters

Camilla WIKENROS, HDkan SAND, Petter WABAKKEN, Olof LIBERG

and Hans C. PEDERSEN

Wikenros C., Sand H., Wabakken P., Liberg O. and Pedersen H. C. 2009. Wolfpredation on moose and roe deer: chase distances and outcome of encounters.

Acta Theriologica 54: 207218.

We examined chase distances of gray wolves Canis lupus Linnaeus, 1758hunting moose Alces alces and roe deer Capreolus capreolus, and recordeddetails of encounters between wolves and prey on the Scandinavian Penin-sula, 19972003. In total, 252 wolf attacks on moose and 64 attacks on roedeer were registered during 4200 km of snow tracking in 28 wolf territories.

Average chase distances were 76 m for moose and 237 m for roe deer, adifference likely due to variation in body size and vigilance between preyspecies. A model including prey species, outcome of the attack, and snow depthexplained 1519% of the variation found in chase distances, with shorter chase

distances associated with greater snow depth and with successful attacks onmoose but not on roe deer. Wolf hunting success did not differ between preyspecies (moose 43%, roe deer 47%) but in 11% of the wolf attacks on moose atleast one moose was injured but not killed, whereas no injured roe deersurvived. Compared with most North American wolf studies chase distanceswere shorter, hunting success was greater, and fewer moose made a standwhen attacked by wolves in our study. Differences in wolf encounters withmoose and roe deer likely result from different anti-predator behaviour andpredator-prey history between prey species.

Grims Wildlife Research Station, Swedish University of Agricultural Sciences, SE-730 91Riddarhyttan, Sweden, e-mail: [email protected] (CW, HS, OL); Department ofForestry and Wildlife Research, Hedmark University College, Evenstad, NO-2480 Koppang,Norway (PW); Norwegian Institute for Nature Research, Tungasletta 2, NO-7485 Trondheim,Norway (HCP)

Key words: anti-predator behaviour, chase distance, hunting success, predator-prey history


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by a predator, ungulate prey species may either

try to outrun the attacking predator, or make a

stand to fend off the predator (Mech 1966,

Kruuk 1972). To outrun a predator, vigilance

and speed is important, while to stand at bay

and fight a predator, body size and condition of

potential prey relative to the predator is crucial

(Mech 1966). Environmental factors such as

snow characteristics (Peterson 1977), light con-

ditions (Kruuk 1972), and habitat cover (Lima

and Dill 1990) may also strongly affect prey vul-

nerability and the chances for escape by prey.

Stalking, typical for hunting in felids, is sen-

sitive to vegetation type and structure (Murray

et al. 1995), whereas cursorial canids may bemore successful when hunting in open habitats

(Wells and Bekoff 1982), and may often exhaust

larger prey by chasing them over long distances

(Kruuk and Turner 1967, Kleiman and Eisenberg

1973). Even among prey species chased by canids,

the use of protective cover may affect the risk of

predation (Kunkel and Pletscher 2000, Dussault

et al. 2005, Hebblewhite et al. 2005, Kauffman et

al. 2007). In temperate regions, the vulnerabil-

ity of prey to predation by wolves Canis lupus,

Linnaeus 1758 has been shown to increase with

greater snow depth (Peterson 1977, Nelson andMech 1986, Huggard 1993, Jdrzejewski et al.

2002). The decision to escape or fight may be in-

fluenced by snow depth as it is more difficult for

some prey species to outrun predators in deep

snow (Paquet 1992).

In North America, wolf chases on ungulates

usually last one to two km (Mech 1966, Peterson

1977). In the classical studies of moose Alces

alces and wolf encounters on Isle Royale, Mech

(1966, 1970) showed that the best strategy for a

moose to survive a wolf attack was to stand at

bay and not try to outrun the attacker. Attempted

escape as an unsuccessful strategy when at-

tacked by wolves has also been reported for mule

deer Odocoileus hemionus (Lingle and Pellis

2002), caribou Rangifer tarandus (Crisler 1956)

bison Bison bison (Smith et al. 2000), elk Cervus

elaphus (MacNulty et al. 2007), and musk ox

Ovibos moschatus (Mech 1988).

Alt hough wolf pre dat ion behavio ur when

hunting ungulates has been studied in numer-

ous areas (Mech 1966, Peterson et al. 1984,

Messier 1994, Hayes and Harestad 2000, Jd-

rzejewski et al. 2000), relatively few reports

have considered (1) actual distances covered

during wolf attacks on different prey species ie

chase distance, and (2) the outcome of encoun-

ters ie hunting success, and the proportion of

ungulates injured but not killed during encoun-

ters with wolves. These aspects may provide fur-

ther insight into the behavioural mechanisms

important for the success of wolf attacks on their

prey.

The objective of this paper is to present data

on chase distances of wolves on two important

prey species during winter in Scandinavia, moose

and roe deer Capreolus capreolus. We examinethe length of chases in relation to wolf-related

(pack size, individual pack effect, number and

age of breeding wolves), prey-related (prey spe-

cies, age class: possible for moose only and body

condition) and a weather-related (relative snow

depth) factor. We describe in detail the outcome

of encounters between wolves and their two prey

species in terms of hunting success, proportion

of injured prey and prey defence behaviour, and

discuss the results in the light of prey anti-pred-

ator behaviour and predator-prey history.

Study area

Sweden and Norway constitute the 837 000 km2

Scan-

dinavian Peninsula, hereafter referred as Scandinavia.

Boreal coniferous forest and alpine areas cover more than

75% of the peninsula. Wolf territories are dominated by

forests consisting of Norway spruce Picea abies and Scots

pine Pinus silvestris, but birch Betula pubescens, B. pendula

and aspen Populus tremula are also available in various

mixtures (Moen 1998, Swedish National Atlas 1991a). The

study area is characterized by intensive forestry and mature

stands are harvested by clear-cutting. This creates a mosaic

of even-aged stands in the landscape together with lakes,

bogs and mires. The terrain is hilly with various visibilities

due to the forest age, but we lack a detailed description of

habitat, topography and visibility at the time of data collec-

tion. Human population density averages 17 inhabitants/km2,

but large areas within the main wolf range contain less

than one inhabitant/km2

(Swedish National Atlas 1991b).

The most important wild prey species for wolves are moose

and roe deer (Sand et al. 2005). Badger Meles meles, beaver

Castor fiber, and in Norway also red deer Cervus elaphus

and potentially wild reindeer Rangifer tarandus are also

available. Within the wolf breeding range, the winter

densities of moose and roe deer range between 0.62.5

moose/km2

and 0.013.5 roe deer/km2, according to estimates

208 C. Wikenros et al.


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from pellet group counts and aerial censuses (Sand et al.

2006a, Sand et al. unpublished data).

In the mid-19th century the Scandinavian wolf popula-

tion probably comprised more than 2000 individuals (Perssonand Sand 1998). By the start of the 20th century few indi-

viduals remained due to intensive persecution and in 1966,

when they became legally protected in Sweden, wolves were

functionally extinct (Haglund 1968, Wabakken et al. 2001).

In the late 1970s wolves re-appeared in south-central Scan-

dinavia and since 1983 they have successfully reproduced

every year, except for 1986 (Wabakken et al. 2001). During

the winter of 20022003 the total population size was esti-

mated at approximately 84100 wolves (including 9 pairs

and 8 packs) and their distribution was concentrated in

the boreal coniferous forest of south-central Scandinavia

(Wabakken et al. 2003). The Scandinavian moose popula-

tion has grown tremendously throughout the 20th century

and has been exposed to an intensive management regime

that replaced most natural mortality with human harvest(Lavsund and Sandegren 1989, Saether et al. 1996). The

Scandinavian roe deer population was considered almost

extinct in the 1920s, but recovered quickly and completely

re-occupied south-central Scandinavia during the early

1980s (Liberg et al. 1994).

Material and methods

Chase distance

During the 19972003 winters, we snow-tracked both

radio-collared (in 15 wolf territories that at least during onewinter had a collared wolf; see Sand et al. 2006b for a de-

tailed description of animal capture and collar use) and

non-collared wolves (in 13 wolf territories) on foot, on skis

and occasionally by snowmobile. The research project was

evaluated and approved by The Swedish Agency of Animal

Welfare (C 266/99) and The Norwegian Agency of Animal

Welfare. Data recorded from snow-tracking included geo-

graphical location and length (km) of tracking route, name

of territory, number of wolves (total and number of breeding

wolves), determination of sex and social position (eg scent-

marking behavior). During the pre-mating season, females

were identified by the presence of vaginal blood in the urine

on snow during estrus, whereas counts of newly-formed

pairs and the number of breeding wolves within packs were

based on their scent-marking behaviour (Mech 1970, Petersand Mech 1975). We used either a compass and map fea-

tures or a handheld GPS unit (Garmin GPS 12/12XL) to

plot wolf tracking routes onto 1:50000 topographic maps.

During snow tracking, all wolf attacks on moose and roe

deer were recorded. A hunting attack was defined as where

lengthening stride patterns for both wolves and moose or

roe deer indicated bounding gaits (fast running). When such

tracks occurred together and local snow conditions indi-

cated they had been made simultaneously, this was re-

garded as an attack (see also Murray et al. 1995 for a

similar definition). The chase distance was defined as the

stretch of fast running by the wolf/wolves and was mea-

sured by plotting the route on a topographic map, or by sav-

ing the route on a handheld GPS unit and then transferring

coordinates to GIS, ArcView 3.3 (ESRI, Redlands, Califor-

nia). An attack was considered successful if a wolf-killed

moose or roe deer was found along the chase route, and as afailure if no carcass was found. We identified species of un-

gulate prey remains by body size, hair, and skeletal re-

mains. We collected mandibles from moose and used them

to determine age by their ontogenetic development and

classified age as calves (< 1 year old) or adults (> 1 year old)

(Markgren 1969). For roe deer, age was determined by com-

paring tooth eruption of mandibles from wolf-killed roe deer

with roe deer of known age (Cederlund and Liberg 1995).

For the current analysis, age was classified into juvenile

(< 1 year old) or adult (> 1 year old).

Snow depth

Snow (depth, density, texture) affects wolf-prey rela-

tionships mainly through restricting movements and may

restrict the chances for successful escape of ungulate prey

(Mech 1970, Peterson and Allen 1974, Peterson 1977,

Huggard 1993). Compared to moose and deer, wolves have a

foot loading (ie foot-load-on-track) that is several times

lighter making wolves better supported in snow of a certain

density (Peterson 1977, Mech and Peterson 2003). There-

fore, we recorded the effect of snow by measuring how

deeply each species sunk into the snow during the attack.

To incorporate the predator-prey-specific constraints of

snow, we analyzed the effect of snow depth by applying the

difference in snow depth (cm) experienced by wolves and

their prey during the attack, hereafter referred to as the

relative snow depth. For example, if the prey sunk 40 cm

and the wolves 20 cm in the snow during the attack the rel-ative snow depth was 20 cm.

Outcome of wolf-prey encounters

When calculating hunting success and outcome of wolf-

prey encounters we used data only from territories with

non-collared wolves. This was done to avoid a bias against

successful attacks as we searched for carcasses using radio

telemetry in territories with radio-collared wolves and

therefore found a higher proportion of successful attacks in

those territories. Each attack was described in terms of the

number of moose or roe deer involved and the outcome of

the attack (successful or failed). We classified prey as

injured if blood, hair or skin were found along the boundinggaits, or if the prey had been pulled to ground by wolves.

Prey defence behaviour was described as either (1) prey

trying to outrun wolves (bounding gaits present), (2) making

a stand (no bounding gaits but including a smaller area of

frequent trampling of both wolves and moose) or (3) a

combination of the two.

Age determination of wolves

We determined the age of breeding adult wolves by a

combination of three methods: (1) known age of captured

animals classified as pups at first capture by the presence

of a growth zone in the tibia (Rausch 1967), (2) tooth wear

Wolf chase distances and prey encounters 209


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of captured adults (Gipson et al. 2000), and (3) construction

of a population pedigree based on DNA analyses for non-col-

lared wolves (Liberg et al. 2005). We used the population

pedigree in combination with a complete set of data on the

chronological order and geographical location of breeding

packs in Scandinavia to identify the year of birth and, thus,

current age for each wolf (Wabakken et al. 2001, Liberg et

al. 2005). Samples for genetic analyses were derived from

either blood or tissue from captured or dead wolves, or from

blood on snow (females in heat) and scats collected during

snow tracking of wolves. If the different methods estimated

different ages for the same animal, we ranked the methods

in order of accuracy as follows: capture of pups > pedigree

construction of birth year > tooth wear of adult wolves. If

results indicated that the birth year could have two or three

alternatives, we used the lower or median age, respectively.

Analyses and statistical procedures

We used the total dataset (n = 316) and the students

t-test to analyze differences in chase distances between

kills of adult and calf moose (the sample size did not allow

for a comparison between roe deer age classes). As data of

snow depth and number of wolves was not always recorded

in the total dataset, we used a reduced dataset ( n = 212)

and an ANCOVA to discriminate between the effects of out-

come of wolf attacks, prey species, number of wolves, num-

ber of breeding wolves, and snow depth on the length of

chases. In order to test whether the main variation in chase

distances explained by model variables was found within or

between wolf territories (temporal pseudo replication) we

included wolf territory (n = 24) as a random variable in the

model. The body condition of temperate ungulates tends to

deteriorate towards the end of the winter (Mech and Peter-son 2003) so we also tested for the effect of body conditions

by including time during the season of the wolf attack (by in-

cluding the number of days from 1 November) in the model.

Age and sex of the breeding wolves were not known in

all cases even in the reduced dataset (n = 212), so we tested

for the potential effect of these factors in a further reduced

dataset (n = 174). In this dataset the ages of the oldest of

the two breeding wolves in each pack were grouped into five

classes (1, 2, 3, 4, and 5 years and older) and used as a con-

tinuous variable together with a factorial variable denoting

the number of breeding wolves present (1 or 2), and the sex

of the breeding wolf (1 = male, 0 = female) present. Test for

interaction (age number of breeding wolves) between

these two variables allowed an evaluation of the potential

effect of sex, in the case of only one breeding wolf present,

and age of the breeding wolf/wolves on the dependent vari-

able. As chase distances were not normally distributed, num-

bers were transformed by ln(x) + 1 but results are presented

as back-transformed data in meters. Variables included in

the model were considered significant at an alpha level of

0.05 and we applied the model building strategy of stepwise

forward inclusion of independent variables. Due to the diffi-

culty of biological interpretation of data we did not include

multiple second-order terms in addition to single factors.

Akaikes information criteria AIC were also calculated and

showed the same model selection results among models as

the one based on traditional significance levels. Analyses

were performed with SPSS version 11.5 for Windows.

Results

Chase distances

A total of 316 chase distances (average 13

chases per pack, range 197, all years pooled) by

wolves were registered including both successful

and failed attacks on moose (n = 252) and roe

deer (n = 64), during approximately 4200 km of

snow tracking for 28 packs (pack size 111

wolves). Successful chase distances ranged from

0 m (one roe deer and nine moose killed while

bedded) to 1.7 km and 2.3 km for moose and roe

deer, respectively. The longest failed chases

were 5 km for moose and 13.7 km for roe deer,but most chase distances were shorter than 400

meters (90% and 69% for moose and roe deer, re-

spectively). Multiple kill of prey was registered

only on one occasion where two roe deer were

killed during one attack by two adult wolves.

There were no significant differences in chase

distances between kills of adult (mean = 82 m)

and calf (mean = 53 m) moose (t = 1.070, df = 1,

nadult = 15, ncalf = 84, p = 0.29).

Factors affecting chase distances

Inclusion of single and multiple variables in

an ANCOVA showed that prey species was the

single most important factor, explaining 12% of

the total variance (F= 24.13, p < 0.001, n = 212),

with an average of 68% shorter chase distances

for moose as compared to roe deer (Fig. 1). The

outcome of an attack (successful or failed) and

the effect of snow slightly increased the predic-

tive power of the model (Table 1). Successful at-

tacks were shorter than failed attacks and chase

distances decreased with an increase in the rela-

tive snow depth (Figs 1 and 2). On average

( SD) wolves sunk 17 12 cm, moose 26 13 cm

and roe deer 21 14 cm during wolf attacks, and

snow depth ranged between 1 and 80 cm. Conse-

quently, according to the model, an increase in

the relative snow depth from 10 to 40 cm, re-

sulted in an average 46% reduction in chase dis-

tance from 140 to 75 m (controlling the effects of

outcome and prey species). In this model, includ-

ing only first-order terms, neither the number of

wolves nor the number of breeding wolves in-



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volved in the attack were significant predictors

of chase distances (Table 1).

In addition, it was shown that two second-or-

der terms were significantly related to chase dis-

tances for wolves on moose and roe deer. Chase

distances differed between moose and roe deer

but were also dependent on the outcome of the

attack. Thus, successful attacks were shorter

than failed attacks for moose (66 versus 123 m)

whereas the reverse was true for roe deer (273

versus 212 m) (Fig. 1). Chase distances also de-

creased with an increase in the number of

wolves involved in successful attacks but in-

creased with an increase in the number of

wolves involved in failed attacks.The multiple model including the three sig-

nificant predictor variables (prey species, out-

come, snow depth) explained 15% of the total


Table 1. Single factors, multiple factors and interaction terms used in an ANCOVA analysis to estimateeffects on the length of chase distances during wolf attacks ( n = 212) on moose and roe deer, in Scandina-

via during winters of 19972003.

Variable(s) in model df F R2

p Power AIC

Constant 356.89

Outcome 1 2.87 0.01 0.09 0.38 356.02

Prey species 1 24.13 0.12 0.00 1.00 335.84

Snow depth 1 12.11 0.06 0.00 0.95 347.01

n wolves 1 1.07 0.01 0.30 0.18 357.82

n breeding wolves 1 3.02 0.01 0.08 0.41 355.87

Prey species +

Outcome 1 6.11 0.13 0.01 0.69 331.74

Snow depth 1 5.83 0.13 0.02 0.67 332.00

n wolves 1 0.04 0.10 0.84 0.06 337.80


Prey species + outcome +

Snow depth 1 5.94 0.15 0.02 0.68 327.76

n wolves 1 0.33 0.13 0.56 0.09 333.40


Prey species + outcome + snow depth +

Outcome prey species 1 5.17 0.17 0.02 0.62 324.54

Outcome snow depth 1 0.01 0.15 0.93 0.05 329.76

Outcome n wolves 1 4.92 0.19 0.01 0.80 321.87

Outcome n breeding wolves 1 0.00 0.16 0.96 0.05 331.21

Prey species snow depth 1 0.38 0.15 0.54 0.10 329.37

Prey species n wolves 1 1.66 0.17 0.19 0.35 328.37

Prey species n breeding wolves 1 2.71 0.17 0.07 0.53 326.25

Snow depth n wolves 1 3.23 0.17 0.07 0.43 326.48

Snow depth n breeding wolves 1 0.52 0.16 0.47 0.11 329.23

n wolves n breeding wolves 1 0.08 0.15 0.78 0.06 329.68

0

100

200

300

400

500

600

700

800

Moose Roe deer

Successful

Failed

Chasedistance(m)

Fig. 1. Chase distances (mean SD) in successful and failedwolf attacks on moose (nsuccessful = 68, nfailed = 92) and roedeer (nsuccessful = 30, nfailed = 22), in Scandinavia during win-ters of 19972003.


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variation found in chase distances. Including

the interaction term with the strongest predic-

tive power (outcome*number of wolves, p = 0.01)

slightly increased the total variation explained

to 19% whereas inclusion of the second strongest

interaction term (outcome*prey species, p =

0.02) explained 17% of the total variation (Table

1). Consequently, most of the variation in chase

distances remained unexplained even when sec-

ond-order terms were included. Inclusion of wolf

territory (n = 24) in the multiple model in addi-

tion to the above significant variables explained

some of the remaining variation (F = 1.69, p =

0.03, R2

= 0.034), but this did not influence the

effect size of the model parameters for prey spe-

cies or outcome. However, it did result in a

non-significant effect of snow depth (F = 1.80,

p = 0.18), indicating that the effect of snow on

chase distances was mainly found at the inter-

territory level. Inclusion of the time during win-

ter (date) of the wolf attack did not increase the

predictability of the multiple model (F = 0.11,

p = 0.74). Finally, in a reduced dataset (n = 174)

neither age of breeding wolves (n = 174, F= 0.40,

p = 0.53), nor the number of breeding wolves or

sex of the remaining breeding wolf (in cases of

only one breeding animal) (F = 1.98, p = 0.14)

were significant predictors of chase distances in

addition to prey species, outcome and snow

depth. The latter three predictor variables also


0

250

500

750

1000

1250

1500

1750

2000

2250

0 5 10 15 20 25 30 35 40 45 50

Successful

Failed

0

250

500

750

1000

1250

1500

1750

2000

0 5 10 15 20 25 30 35 40 45 50

Snow depth (cm)

(a)

(b)

Chase

distance

(m)

Fig. 2. Chase distances (m) in relation to snow depth (measured as the difference between the depth prey and wolves hadsunk into the snow) during wolf attacks on (a) moose (nsuccessful = 68, nfailed = 91) and (b) roe deer (nsuccessful = 30, nfailed = 22), inScandinavia during winters of 19972003. One wolf attack on moose, with chase distance 5000 m at 40 cm difference in snowdepth, is not shown in Fig. 2a.


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remained significant in this reduced dataset and

with approximately the same size of the model

parameter estimates as in the larger dataset

(n = 212).


Detailed reconstruction of the outcome of

wolf and moose encounters was available for 40

wolf attacks involving 66 moose (Fig. 3) in 19

wolf territories. Four of the 66 moose (6%) were

confirmed to have made a stand, two of them

(age unknown) directly when confronted with

the wolves and two (cow and calf) after a 1 km

long chase. All four survived unharmed. Forty-two moose (64%) escaped unharmed by fleeing

immediately and seven more (11%) after being

injured by the wolves, as we found blood, hair or

skin along the flight track. Two of the injured

moose were pulled to the ground one and six

times, during chases that lasted 2 km and 5 km,

respectively, but both moose managed to get up

and outrun the wolves. We do not know if those

moose later died due to the wounds they sus-

tained during the attack. Seventeen of the 66

moose (26%) were killed, two of them (one adult,

one calf) while bedded, and 15 after being chased

and caught by the wolves. Nine of these were

killed during first contact (all calves) and the

other six (two adults, four calves) after repeated

contacts with wolves during the flight. Three of

the six moose that were killed after repeated

contacts were also pulled to the ground while

trying to escape the wolves.

A total of 32 wolf attacks on roe deer were dis-

tributed over 14 wolf territories. Fifteen (47%) of

these attacks were successful. In 23 of the 32 at-tacks the number of roe deer attacked was also

registered resulting in a total of 36 roe deer.

Eight of the 36 roe deer attacked were killed, re-

sulting in a hunting success of 22% per individual

roe deer attacked. Detailed description of the out-

come of wolf attacks on roe deer was available for

ten attacks (Fig. 4) involving 14 individuals. No


62

chased by wolves

22

physical contact with wolves

66

moose attacked by wolves

13

injured (loss of hair/blood/skin)

5

pulled to ground

3

killed

( 1 adult, 2 calves)

40

escaped

unharmed

3

killed

(1 adult, 2 calves)

5

escaped

injured

2

escaped

injured

2

made a standand survived

9

killed at first contact

(9 calves)

2

stopped and made

a stand

Fig. 3. Outcome of encounters between moose and wolves in 40 attacks in Scandinavia during winters of 19972003. Dashedarrows indicate moose that survived wolf attacks and filled arrows indicate killed moose.


8/12

roe deer made a stand when wolves approached.

Eight roe deer outran the wolves and escaped un-

harmed. One roe deer was killed while bedded,four were killed at first contact during flight, and

one was killed after repeated injuries during

flight. No roe deer injured during an attack sur-

vived. Wolf hunting success on roe deer was simi-

lar to that of moose, both when calculated as the

proportion of successful attacks (moose: 43%, roe

deer: 47%, c2

= 0.14, df = 1, p = 0.71) and as the

proportion of prey animals killed out of all prey

animals involved in the attacks (moose: 26%, roe

deer: 22%, c2

= 0.16, df = 1, p = 0.69).

Discussion

Chase distances

Chase distances of Scandinavian wolves on

moose and roe deer showed large variation but

were mostly shorter than 400 m. This is in the

lower range of distances reported in most North

American wolf studies including white-tailed

deer Odocoileus virginianus with 600 m and

1900 m for failed attacks, during two successive

winters, and 2100 m during both winters for suc-

cessful attacks (Kolenosky 1972). Mech (1966)found that wolves on Isle Royale most often

(78%) gave up after less then 800 m when chas-

ing moose, with the longest chase being 4.8 km.

Paquet (1989) recorded average distances of 886

m, 159 and 115 m for successful chases on

moose, deer and elk, respectively, in Manitoba,

Canada, whereas Hebblewhite et a l. (2005)

showed that the average chase distance by

wolves on elk in Alberta, Canada was 260 m and

ranged between 10 and 1700 m.

Causes of variable chase distances

Defense strategies to predator attacks are

likely to differ between moose and roe deer with

the larger moose being able to confront the at-

tacking predator, an option not open to roe deer

(roe deer/moose size ratio 1:15 of adult and 1:6 of

calf moose). Roe deer are therefore totally de-

pendent on their vigilance, their initial accelera-

tion speed, and their endurance to successfully

escape wolves. Mech and Korb (1978) reported


1

killed while bedded

(adult)13

chased by wolves

5

physical contact with wolves

14

roe deer attacked by wolves

1

injured (loss of hair/blood/skin)

0

pulled to ground

1

killed

(age unknown)

8

escaped

unharmed

0

made a stand

4

killed at first contact

(2 adult, 2 age unknown)

0

stopped and made

a stand

Fig. 4. Outcome of encounters between roe deer and wolves in 10 attacks in Scandinavia during winters of 19972003. Dashedarrows indicate roe deer that survived wolf attacks and filled arrows indicate killed roe deer.


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that one white-tailed deer fled for more than 21

kilometres without being killed, and in our study

wolves chased one roe deer for almost 14 km be-

fore giving up the attack. Once caught up by

wolves, small deer species like white-tailed deer

and roe deer seem to be doomed, which is sup-

ported by our study where all roe deer that were

in physical contact with wolves were killed.

Considering that moose and roe deer are rad-

ically different in meat yield, and that hunting

success was shown to be approximately equal for

both prey species, longer chase distances might

be expected for moose compared to roe deer.

However, all moose attacked are not vulnerable

to wolf predation (Mech 1970, Sand et al. 2005),and because of the higher risk involved in at-

tacking moose compared to smaller deer (Weaver

et al. 1992, Mech and Peterson 2003), wolves

may continuously evaluate the vulnerability of

individual moose during attacks and terminate

the attack on certain individuals.

Snow depth

Several studies have shown that snow depth

affects the vulnerability of ungulates to preda-

tion (Peterson 1977, Nelson and Mech 1986,Jdrzejewski et al. 1992, 2002, Huggard 1993), a

finding consistent with our study. More snow

generally resulted in shorter chases for both

prey species irrespective of outcome of the at-

tack, but we lacked data on roe deer in snow

deeper than 20 cm. Moose vulnerability to pre-

dation by wolves has been shown to increase at

snow depths of more then 75 cm (Peterson 1977).

During our study winters snow depths exceeded

this depth in only one wolf territory. Therefore,

it is likely that the constraint of snow will be

much more marked at snow depth greater than

what was found for majority of wolf-prey en-

counters in this study. In our analyses, snow

depth was measured as the difference between

the depth prey and wolves sunk into the snow

during the attack, which enabled us to incorp-

orate the predator-prey-specific constraints of

snow. Despite the relatively limited variation

in snow depth, our results conform to earlier

findings that wolves have an advantage over

prey in snow due to their lower foot-load (ratio of

body mass to foot area), in this case resulting in

shorter chase distances with increased snow

depth.

Other factors important for chase distances

Our results showed that the number of wolves

involved in an attack was negatively related to

chase distances, but only for successful attacks.

Inspection of data showed that this relationship

was a statistical artifact that was related to dif-

ferences in chase distances between prey spe-

cies. As chase distances on roe deer were longer

than on moose, and we had a maximum of three

wolves involved in attacks on roe deer, this re-sulted in a negative relationship between chase

distances and number of wolves during success-

ful attacks. Consequently, this study provided

no support for the assertion that the number of

wolves involved in the attack was an important

factor affecting chase distances on moose and

roe deer.

Although several factors signif icantly ex-

plained variation in chase distances, most of the

variation (8183%) remained unexplained and

may be attributed to several predator-, prey-

and environmentally-related factors. For exam-ple, age and sex of breeding wolves have been

shown to affect hunting success on Scandina-

vian moose (Sand et al. 2006b). Therefore, we as-

sumed that individual characteristics also would

be important affecting chase distances if wolves

of greater age and experience learn how to kill

prey more efficiently. In contrast, this study (us-

ing largely the same dataset as in Sand et al.

2006b) found no support for our assumption that

the age of breeding wolves was an important fac-

tor affecting chase distances. Nor did we found

evidence that the time during winter, a proxy for

general condition of prey, explained further

variation in chase distances.

One factor expected to have implications for

the type and outcome of interactions between

predators and prey is the physical features of

the landscape. Landscape heterogeneity is likely

to affect the visibility and influence the distance

at which prey and predators may reach visual

contact (Mills et al. 2004, Kauffman et al. 2007).

However, our study area in Scandinavia is domi-



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nated by a mixture of relatively small and dense

coniferous forest stands in variable age classes

and tree species mixtures. Therefore, in general

we would predict much shorter detection dis-

tances than in other predator-prey systems hav-

ing a larger proportion of open landscapes, for

example Yellowstone, USA (Boyce et al. 2003).

Interestingly, chase distances on elk was reported

to average 980 m in this system (Kauffman et al.

2007). Although landscape features of our study

system offers a relatively low degree of visibil-

ity, we suggest that between-patch variability in

visibility is likely responsible for a significant

portion of the unexplained variation in chase

distances found. Regrettably, this parameterwas not recorded during field work, nor avail-

able at adequate resolution from GIS-data. In

addition, individual characteristics like age, sex

and body condition of prey animals involved in

failed attacks may also contribute to some of the

unexplained variation in chase distances found.


Adult moose were generally more difficult to

kill for wolves once caught up than calves that inturn were more difficult to kill than roe deer.

This was likely a result of size difference and the

capability of defence of the different prey. In

contrast, we found no difference in chase dis-

tances for successful attacks between calf and

adult moose.

The proportion of injured moose, 11%, was

similar of that reported from Denali, Alaska

(13%, Mech et al. 1998) but higher than reported

from Isle Royale, USA (1%, Mech 1966). Hunting

success on moose was greater than that reported

from North America (Mech 1966, Mech et al.1998) but our data indicated that only a small

proportion of the moose attacked by wolves made

a stand while, for example on Isle Royale, up to

40% of the moose showed this behaviour when

confronted with wolves (Mech 1970, Peterson

1977). The relatively high hunting success rate,

short chase distances, and a low proportion of

moose that made a stand are likely to be a result

of moose being a predator-naive prey to wolves, a

result of predator-prey history and man as the

main mortality factor for moose during the last

century in Scandinavia (Sand et al. 2006a).

We suggest that differences in chase distances

between prey species are explained by different

anti-predator behaviour partly due to variation

in size and vigilance in moose and roe deer. Com-

pared to moose, roe deer may be a less preda-

tor-naive prey species since their major predator,

the Eurasian lynx, reoccupied south-central

Scandinavia 3040 years before the return of

wolves to this region (Liberg 1998). In contrast to

the cursorial wolf, the lynx is a stalking predator

likely forcing roe deer to adopt a more vigilant be-

haviour, as compared to moose, in response to

the return of the main predator.Acknowledgements: We thank a number of people who helpedwith snow tracking of wolves, especially C. Aronson, B.Broman, B. Dahlen, J. Dahlen, H-E. Eriksson, G. Jansson,J. Johansson, K. Johansson, M. Johansson, P. Johansson,T. Mellgren, S. Nordgren, D. Palm, M. Rapp, H. Rrnning,M. Sandstrm, O. K. Steinset, T. Holm Strrmseth, A. StDhland R. Wiklund. M. Apollonio, J. W. Laundr, R. Petersonand one anonymous reviewer provided valuable commentson an earlier draft of this paper. This study was supportedby the Swedish Environmental Protection Agency, the Asso-ciation for Hunting and Wildlife Management, the WorldWildlife Fund for Nature (WWF Sweden), the Swedish Uni-

versity of Agricultural Sciences, the Norwegian Directoratefor Nature Management, the Norwegian Research Council,the Norwegian Institute for Nature Research, Hedmark

University College, the County Governor of Hedmark,Borregaard Skoger AS, Glommen Skogeierforening, Olleand Signhild Engkvists Stiftelse, Carl Tryggers Stiftelse,the Swedish Carnivore Association, Stor-Elvdal, Trysil, Cmotand Csnes Municipalities.

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