Heurich, M., Moest, L., Schauberger, G., Reulen, H., Sustr, P., and Hothorn, T. (2012). Survival and causes of death of European Roe Deer before and after Eurasian Lynx reintroduction in the Bavarian Forest National Park. Eur. J. Wildl. Res. 58: 567-578.

Keywords: 8DE/analysis/Bavarian Forest National Park/Eurasian lynx/forest/lynx/Lynx lynx/mortality/National Park/predator-prey/predator-prey interaction/reintroduction/roe deer/survival/survival rate/Capreolus capreolus

Abstract: The return of the Eurasian Lynx to Central Europe has led to a number of conflicts. A primary subject of discussion involves its predation on other wildlife species. Here, we investigated the influence of lynx on its main prey, Roe Deer, in the Bavarian Forest National Park in south-eastern Germany. We compared the survival rates of deer before and after reintroduction of lynx. The analysis is based on data from 1984 to 1988 and 2005 to 2008 of 88 and 99 radio-collared Roe Deer, respectively. During the first period, 35 deer deaths were documented; during the second period, 41 deaths were documented. The causes of death in the second period were lynx 44%, road kill 15%, hunting 12%, and other causes 29%. We used the Cox model to determine the influence of covariables on the hazard rate, which made it possible to consider interactions between the variables. The resulting model includes the four main effects sex, age, presence of lynx, and severity of first winter, and the three interactions-presence of lynx:sex, age:severity of first winter, and sex:severity of first winter, which had a statistically significant influence on Roe Deer survival.

ORIGINAL PAPER

Survival and causes of death of European Roe Deerbefore and after Eurasian Lynx reintroductionin the Bavarian Forest National Park

Marco Heurich & Lisa Möst & Gunther Schauberger &

Holger Reulen & Pavel Sustr & Torsten Hothorn

Received: 16 September 2010 /Revised: 18 December 2011 /Accepted: 27 December 2011 /Published online: 26 January 2012# Springer-Verlag 201

Abstract The return of the Eurasian Lynx to CentralEurope has led to a number of conflicts. A primary subjectof discussion involves its predation on other wildlifespecies. Here, we investigated the influence of lynx onits main prey, Roe Deer, in the Bavarian Forest NationalPark in south-eastern Germany. We compared the survivalrates of deer before and after reintroduction of lynx. Theanalysis is based on data from 1984 to 1988 and 2005 to2008 of 88 and 99 radio-collared Roe Deer, respectively.During the first period, 35 deer deaths were documented;during the second period, 41 deaths were documented. Thecauses of death in the second period were lynx 44%, road kill15%, hunting 12%, and other causes 29%. We used the Coxmodel to determine the influence of covariables on the hazardrate, which made it possible to consider interactions betweenthe variables. The resulting model includes the four maineffects sex, age, presence of lynx, and severity of first winter,and the three interactions—presence of lynx:sex, age:severityof first winter, and sex:severity of first winter, which had astatistically significant influence on Roe Deer survival.

Keywords European Roe Deer . Eurasian Lynx . Survival .

Predation .Mortality . Lynx lynx .Capreolus capreolus

Introduction

In Central Europe, large predators had been extirpatedfrom the landscape by the mid-nineteenth century. Thus,for more than 150 years, the human population there hadno experience coexisting with large predators. In the pastfew decades, some species of large predators have beenactively reintroduced to Central Europe—the first beingthe Eurasian Lynx (Lynx lynx; Festetics 1980).

Although the behaviour of lynx is inconspicuous, theirreintroduction was accompanied by a great deal of contro-versy (Egli et al. 2001, Hunziker et al. 2001). One majorcause of concern was the lynx predation on domestic ani-mals, but this problem could usually be alleviated throughthe development and implementation of preventive measuresand the introduction of compensatory programmes (reviewedin Breitenmoser et al. 2005). A much greater conflict is thecompetition of lynx with humans as hunters. Roe Deer is themain prey hunted by lynx in most parts of Europe. Dependingon local conditions, Red Deer, chamois, or reindeer mayalso be of importance (see review in Breitenmoser andBreitenmoser-Würsten 2008). These are also the speciesof highest interest for human hunters, whereby the prominenthunting system in Central Europe, with its territorial huntingconcessions, which increases the conflict between hunters andlynx. This has led to a number of illegal shootings of lynx(Jedrzejewski et al. 1996, Cerveny et al. 2002, Breitenmoserand Breitenmoser-Würsten 2008).

To address the conflicting interests of human hunters andpredators, the impact of predators on the populations of wildungulates in Europe needs to be determined. Most reports

Communicated by C. Gortázar

M. Heurich (*)Bavarian Forest National Park,Freyunger Straße 2,94481 Grafenau, Germanye-mail: marco.heurich@npv-bw.bayern.de

L. Möst :G. Schauberger :H. Reulen : T. HothornLudwig Maximilians Universität München, Universität München,Geschwister-Scholl-Platz 1,80539 München, Germany

P. SustrSumava National Park,Plzen, Czech Republic

Eur J Wildl Res (2012) 58:567–578DOI 10.1007/s10344-011-0606-y

2

on proliferating wild ungulate populations and relateddamage to forest regeneration originate from the cultivatedand intensively managed forests of Western and CentralEurope and from the Eastern United States (reviewed inCôté et al. 2004), where large predators have been almostcompletely driven to extinction. The influence of lynx onits prey has been studied in Switzerland (Breitenmoser andHaller 1987, Molinari-Jobin et al. 2002, Breitenmoser andBreitenmoser-Würsten 2008), Poland (Okarma et al. 1997),and Norway (Nilsen et al. 2009b). The results of thesestudies vary greatly: in some areas, the influence of lynxis insignificant and in others it is pronounced, and insome cases it can differ considerably within a given studyarea. The reasons for these observations are many-facetedsince predation is dependent on various factors, such asclimate, nutritional base, diseases, competition, and landuse by humans (Breitenmoser and Breitenmoser-Würsten2008). The productivity of the environment, which inturn determines prey density, appears to be especiallyimportant (Melis et al. 2009, Nilsen et al. 2009b).

To determine the extent to which lynx are capable ofinfluencing the populations of their wild prey is of utmostimportance for understanding the role of lynx as predators inthe ecosystem. This information provides a basis fordiscussion with the relevant local interest groups andfor the development of management plans. Environmen-talists and animal protection advocates often quote thetheory that lynx only kill a very small proportion of theRoe Deer population and that the losses are less significantthan those caused by traffic incidents. In contrast, huntersargue that the influence of lynx is quite substantial and thatthe behavioural changes induced by their presence have madeRoe Deer more difficult to hunt (Heurich et al. 2007).

One possible method to study the influence of a predatoron its prey is to compare the populations of prey speciesin areas with and without the presence of predators.Another possibility is to study periods before and afterthe re-introduction or natural return of a predator. Wechose the second approach because we were able to compareRoe Deer survival before and after the re-colonization of lynx.In this study, we tested the following predictions: (1) Sincelynx predation can have an impact on Roe Deer populations inother places (Breitenmoser and Haller 1987, Jedrzejewskaand Jedrzejewski (1998), Breitenmoser et al. 2010), weexpect that Roe Deer survival should decrease after lynxre-colonization. (2) Severe winters can strongly affectpopulation dynamics of Roe Deer. Especially snow depthsabove 30 cm restrict the movement of the animals, and evenhigher snow packs can lead to malnutrition because importantplants for browsing cannot be accessed (Danilkin 1996,Holand et al. 1998). Therefore, we expect that harshwinters should negatively impact Roe Deer survival. (3)Since the sex ratio of free-ranging Roe Deer populations

shifts to a higher proportion of females (Ratcliffe andRowe 1985, Cobben et al. 2009), we expect that femaleshave a higher survival than males. (4) Since mortality ofjuvenile Roe Deer is higher than that of prime-age animals(Gaillard et al. 1997, Gaillard et al. 1998), we expect youngindividuals to have a lower survival.

Material

Description of the study area

The Bavarian Forest National Park is situated in south-eastern Germany along the border to the Czech Republic(49° 3′ 19″ N, 13° 12′ 9″ E). Designated in 1970, it was thefirst national park in Germany. Since its expansion in 1997,the national park now covers an area of 240 km2. Adjacentto the park, on the Czech side of the border, lies the SumavaNational Park with its 640 km2. These protected areas areembedded within the Bavarian Forest Nature Park(3,070 km2) and the Sumava Landscape Protection Area(1,000 km2). In its entirety, the area is known as theBohemian Forest Ecosystem.

The area is mountainous, with a variation in elevationbetween 600 and 1,453 ma.s.l. The mean annual tempera-ture is between 6.5°C in the valleys and 3°C along the ridgesand at higher elevations. The mean annual precipitation isbetween 830 and 2,230 mm, a considerable amount ofwhich occurs as snowfall. Snow cover persists for 7 to8 months at the higher elevations and for 5 to 6 months inthe valleys.

Within the park, three major forest types exist: above1,100 m are sub-alpine spruce forests with Norway Spruce(Picea abies L.) and some Mountain Ash (Sorbus aucupariaL.) (16% of the area); on the slopes, between 600 and1,100 m altitude, are mixed montane forests with NorwaySpruce, White Fir (Abies alba MILL.), European Beech(Fagus sylvatica L.), and Sycamore Maple (Acer pseudo-platanus L.) (68% of the area). In wet depressions, oftenassociated with cold air pockets in the valley bottoms,spruce forests with Norway Spruce, Mountain Ash, andbirches (Betula pendula ROTH. and Betula pubescensEHRH.) occur (16 % of the area) (Heurich and Neufanger2005). Since the mid-1990s, the forests of the national parkhave been affected by massive proliferation of the sprucebark beetle (Ips typographus). By 2007, this had resulted inthe death of mature spruce stands over an area amounting to5,600 ha (Heurich and Neufanger 2005).

Winter severity

To describe the impact of winter on the mortality of RoeDeer, we calculated a winter severity index (WSI) using data

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from the Waldhäuser weather station (945 m) located in thecentre of the study area (Fig. 1). The WSI was developed inthe early 1970s for white-tailed deer in North America(Verme and Ozoga 1971). It is calculated by adding thenumber of days with 18 in. or more of snow on the groundto the number of days when the minimum temperature is ≤0Fbetween December 1 and April 30. Each day on which bothconditions occur simultaneously is given two points. At theend of the winter, all points are added up, resulting in the WSIfor the entire winter. A winter with a WSI <50 is consideredmild, from 50 to 79 is considered moderate, from 80 to 99 isconsidered severe, and >100 is considered very severe(Kohn 1978).

Lynx presence in the research area

Owing to intense hunting pressure and persecution of itsprey, the Eurasian lynx had become extinct in Germany,including in the Bavarian–Bohemian border region. Here,the population had been extirpated by the mid-19th century.The last animals on the Bavarian side of the border wereshot in 1846 and on the Czech side in 1890 (Cerveny andBufka 1996; Heurich and Wölfl 2002).

Lynx was initially reintroduced to Central Europe in theBavarian Forest National Park between 1970 and 1974 withthe release of an estimated 5 to 10 animals. However,although these individuals quickly dispersed out of thestudy area (see number of registered lynx tracks in Fig. 2),reports confirm their continued presence in neighbouringregions well into the 1980s. Since these reintroductionswere performed in secrecy, the conditions under whichthey were carried out are not known (Wotschikowsky 1978,Festetics 1980).

From 1982 to 1987, lynx were reintroduced again, thistime in the adjacent Bohemian Forest on Czech territory.There, 17 lynx (11 males, 6 females) were released. Theseanimals had been captured in the wild in the SlovakianCarpathians. The reintroduction was successful, and thepopulation spread to the Bavarian Forest and fartherwestward from the 1990s on (Koubek and Cerveny 1996;Cerveny and Bufka 1996; Fig. 2).

Wildlife management in the Bavarian Forest National Park

Among the objectives of the Bavarian Forest National Parkis the promotion of undisturbed dynamics of naturalcommunities. Accordingly, one of the principles is notto control the wild ungulate population through humanintervention. However, somemanagement becomes necessaryif certain national park goals or the rights of adjacentprivate landowners suffer considerable negative impacts.To keep disturbances to a minimum, necessary controlmeasures are practised only in the so-called wild ungulatemanagement zone, which also serves as a buffer zone andarea of transition to the cultural landscape. Also, the numberof wildlife feeding stations has been reduced since thefounding of the national park; since 1990 feeding stations areno longer maintained (Fig. 3).

In the 1980s, this management zone comprised approxi-mately 58% of the study area. This means that wildlife controlwas excluded from an area of 57 km2. During the study, anaverage of 56 Roe Deer were shot annually (Fig. 4).

During the more recent study period, the wild ungulatecontrol zone comprised only 20% of the study area. Therefore,the area fromwhichwildlife regulationwas excluded increasedto 103 km2. The mean number of animals shot per year in that

Fig. 1 The winter severityindex (WSI) in the studyarea in the Bavarian ForestNational Park from 1970/1971to 2008/2009. The WSI wascalculated using data from theWaldhäuser weather station(945 m) located in the centre ofthe study area. WSI values,<50, mild winter; 50–79,moderate winter; 80–99, severewinter; and >100, very severewinter. The periods of ourstudy are indicated: period I(1984–1988) and period II(2004–2008)

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period was 30 (Fig. 4). The density of Roe Deer in the area isestimated to vary between 1/km2 at high elevations and 5/km2

in the valleys. The wildlife management in the study area isdescribed in more detail in Heurich et al. (2011).

Methods

Field work

Field work was performed during two separate periods:period I (1984–1988) and period II (2004–2008). Duringboth periods, the Roe Deer were captured during the wintermonths (October to March) using wooden box traps. The

animals were lured into the traps with feed (pomace, maize,or silage). The traps were set during the evening andinspected the following morning. A captured deer wasgrasped by the legs, pulled from the trap, and held firmlyby its legs. Body measurements and weight were recordedand transmitters were attached within 5 min (Heurich 2011);therefore, it was not necessary to immobilize the animals.Animal handling was performed in compliance with Germanlaws and regulations.

In period I, 88 Roe Deer were caught and equipped withconventional VHF collars. The animals were aged accordingto their tooth wear and assigned to the following classes(Rieck 1970): fawn, yearling, or adult. In the analysis, theanimals were classified only as either young (fawn and

Fig. 2 The number ofregistered lynx tracks found bythe park service per year in thestudy area in winter from 1969to 2005. The periods of ourstudy are indicated: period I(1984–1988) and period II(2004–2008). There was anunsuccessful lynx release in1970 with an increase in tracknumbers until 1974. After thatyear, lynx tracks were foundonly infrequent. A secondreintroduction took placebetween 1982 and 1987 in theadjacent Czech Republic. As aconsequence, the number oftracks increased at thebeginning of the 90s

Fig. 3 The number of activewinter feeding stations withinthe study area from 1970 to2008. The periods of ourstudy are indicated: period I(1984–1988) and period II(2004–2008). Period I and IImark the time span of the twodifferent study periods. Inperiod I, the number of feedingstations was strongly reduced,in period II, all feeding wasstopped according to nationalpark philosophy

570 Eur J Wildl Res (2012) 58:567–578

yearling) or adult. If an individual was captured as a fawn/yearling, it was reclassified as a yearling/adult in May of thesubsequent year and as an adult in May of its third year.Mortality was checked once a week. In period II, 95 animalswere caught and equipped with GPS-GSM collars withinternal mortality sensors. If the animals were not activefor more than 6 h, 12 GPS positions were measured andsent via SMS. Subsequently, the animals were located in thefield, and the cause of death was determined. In the case ofGPS failure, the status of the animals was checked via VHFthree times a week. Dead animals were assigned to theclasses: lynx kill, road kill, regular hunting, other cause ofdeath, collar detached, collar failure.

Data analysis

The Cox proportional hazards model, which describes thehazard rate by means of a linear function of covariates, and asurvival regression tree were used to adjust for other cova-riates influencing the survival times of Roe Deer (Cox1972). For the proportional hazards analysis, main effects(presence of lynx, age, sex, severity of first winter) and\two-way interactions define the full model. Variable selectionbased on the Akaike information criterion (AIC) was used toselect the best model for interpretation. The validity of theproportional hazard assumption for the variables included inthe model was tested by assessing the time dependency of theregression coefficients (Grambsch and Therneau, 1994).

As a nonparametric alternative, a conditional survivaltree (Hothorn et al. 2006a) was used to split the observationsinto distinct subgroups with respect to the observed survivaltimes by means of cutpoints in the covariates. Such regression

tree models explain variation in the censored responsevariable as a function of the covariates. One covariate isselected from all available covariates by maximizing theassociation with the response via a permutation test(Hothorn et al. 2006a), and a split point that separates theresponse values into two homogeneous groups is estimated bya maximally selected statistical test (Hothorn and Zeileis2008). The split point is determined by a numerical value ofthe covariate. Once the split point has been estimated for aselected covariate and the groups have been defined, eachgroup is further separated with new covariates and split points.A stopping criterion based on permutation tests is used to stopthe recursive splitting procedure (Hothorn et al. 2006b).

Results

Description of the data

In the first study period, 88 Roe Deer were caught andcollared; 56 were females, 46 were adults, 14 were yearlings,and 22 were fawns. The ages of six animals were notdocumented, and these animals were therefore not usedin the analysis. In the second study period, 99 Roe Deerwere caught and collared; 42 were females, 55 wereadults, 8 were yearlings, and 36 were fawns (Table 1).

In the course of the first study period, 35 animals (39.8%)were found dead. The cause of death was determined onlyfor traffic accidents and hunting. Since during that period,the locations of the animals were determined only once perweek, other causes of death could not be assessed accuratelyand were, therefore, not taken into consideration (Table 2).

Fig. 4 The number of Roe Deer hunted within the study area. The periods of our study are indicated: period I (1984–1988) and period II (2004–2008)

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During the second study period, 42 (42.4%) of theanimals were found dead. The most common cause ofdeath was predation by lynx, followed by vehicle trafficand hunting. Other known causes of death and causesthat could not be determined (because the cadavers hadbeen scavenged by other animals or because a mortalitysignal had not been sent) accounted for approximately30% of the deaths. The annual causes of death are shownin Table 3.

Cox proportional hazards model

The general model included the four main effects (presenceof lynx, sex, age, and severity of first winter) and all two-way interactions. The interactions lynx:sex, age:severity offirst winter and severity of first winter:sex had a statisticallysignificant influence on Roe Deer survival (Table 4). Themain effect of a factor cannot be removed from the modelwhen this factor is involved in an interaction. Therefore,because sexes responded differently in terms of survival tolynx and to winter severity, we concluded that survivalpatterns differed between sexes. For a male animal in thesecond study period, the interaction lynx presence:sex isstatistically significant and is characterized by a factor of5.850. As a consequence, the survival of a male Roe Deer islower in the period with lynx presence. The interaction age:severity of first winter indicated that the hazard rateincreases by the additional factor of 1.012 if the severityof a juvenile's first winter increases by one unit. This showsthat above all, the survival of young animals is lower if thefirst winter is more severe. Furthermore, owing to the inter-action severity of first winter:sex, an increase in winterseverity by one unit causes for males a decrease in thehazard rate by a factor of 0.99. This indicates that winterseverity does not have a strong impact on males.

We tested the validity of the proportional hazards hypoth-esis for the variables and interactions included in the modelwith the aid of the function cox.zph from the R packagesurvival. None of the variables were significant. The nullhypothesis, which favours the validity of the proportionalhazards hypothesis, is not significantly invalidated by any ofthe variables. Therefore, its legitimacy may be consideredconfirmed.

A clear difference between the two study periods is theextended no-hunting zone and the reduced hunting duringthe second study period. To account for this difference, werefitted the above Cox model and censored all Roe Deer thatdied because of hunting (Table 5). The two models are quitesimilar with regard to directions of influence and signifi-cance levels. The interaction severity of first winter:sex ismissing in the refitted model, but it was not significant in theprevious model. The interaction presence of lynx:sex wasstill highly significant and age:severity of first wintershowed a lower p value than in the previous model. All inall, the interpretations based on the refitted model remainedapproximately the same as in the previous model and there-fore cannot be caused mainly by the differences in thehunting situation. Therefore, we used the first Cox modelfor further interpretations and explanations.

After implementation of the classification tree, the mostsignificant difference was found for the variable lynx presence(Fig. 5). Consequently, the data set was differentiatedaccording to this variable. For Roe Deer from the firststudy period, none of the variables were significantlydifferent and were therefore not differentiated further.For animals from the second study period, the subsequentdifferentiation is based on the variable age. During this period,the survival rates of the juveniles were statistically signifi-cantly lower than those of the adults.

Discussion

Ten animal species have been described as predators of RoeDeer, but only three are known to be capable of preying onthe deer to a significant extent: fox, wolf, and lynx (Aanes etal. 1998). Various studies indicate that foxes mostly killfawns in the first 2 months after birth. In Norway andSweden, 10–58% of the fawns are consumed by foxes

Table 1 The distribution of collared Roe Deer during the two studyperiods according to sex and age

Studyperiod

Females Adults Yearlings Fawns

1984–1988 56 (63.6%) 46 (56.1%) 14 (17.1%) 22 (26.6%)

2005–2008 42 (42.4%) 55 (55.6%) 8 (8.1%) 36 (36.4%)

Table 2 Sex and cause of death of collared Roe Deer found dead during the two study periods

Study period Total number of deaths Number of dead females Death caused by

Lynx Traffic Hunting Other causes

1984–1988 35 24 (68.6%) 0.0% 6 (17.1%) 5 (14.3%) 24 (68.6%)

2005–2008 42 16 (38.1%) 18 (42.9%) 6 (14.3 %) 5 (11.9%) 13 (31.0%)

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(Aanes and Andersen 1996, Panzacchi et al. 2007, Lindströmet al. 1994). Since the fawns in our study were not fitted withtransmitters until after the first winter when they were at least6 months old, we could not draw conclusions on survival ratesin the first months after birth. Foxes also kill Roe Deer in deepsnow during the winter (Cederlund and Lindström 1983), butthis occurs only rarely. In our study, we did not observepredation of adult deer by fox.

When large predators occur within the range of Roe Deer,their predation has a marked effect on the deer populations,and lynx and wolf are the most important predator species.In various forests, 20–30% of the deer population maysuffer wolf predation (Kucherenko and Zubkov 1980,Bromlei and Kucherenko 1983 both cited in Danilkin1996). After the removal of all predators in an area of4,500 km2, the Roe Deer population increased by 50%(Lavov, 1974, 1982; cited in Danilkin 1996). Heavy impactsof predation on Roe Deer by wolves have also been docu-mented in studies from Poland and Italy (Okarma et al., 1997;Jedrzejewski et al., 2002; Gazzola et al., 2007). Furthermore,Jedrzejewska and Jedrzejewski (1998) have shown in easternPoland that predators are capable of limiting Roe Deer to

numbers markedly below the habitat-carrying capacity, espe-cially when lynx and wolf occur in the same area simulta-neously and the effects of the predators are cumulative.As a result, the occurrence of large predators has aninfluence on the survival rates of the deer. Roe Deer atprime age without predators have a consistently high year-ly survival rate of 0.82–0.97, and their survival ratedecreases when large predators occur in an area (Gaillardet al 1993, Focardi et al. 2002, Cobben et al. 2009).Nilsen et al. (2009b) determined a similar survival rateof 0.8 in areas without predators, the rate decreased tobelow 0.7 in areas with hunting, lynxes, and wolves. Wealso found similar survival rates of 0.79 without lynxpredation and 0.61 with lynx predation.

Several groups have investigated the influence of lynx onits prey. Between 1983 and 1985, 12% of Roe Deer deathswere caused by lynx in the north-west Alps of Switzerland(Breitenmoser and Haller 1987), the numbers for theSwiss Jura, and Poland, were 30% and 39%, respectively(Molinari-Jobin et al. 2002, Okarma et al. 1997). Thehighest death rate of 62% reported for north-west Alps ofSwitzerland between 1997 and 2001 (Breitenmoser and

Table 3 Annual causes of deathand total mortality rates ofcollared Roe Deer

Cause of death 1984 1985 1986 1987 1988 2005 2006 2007 2008

Lynx 0% 0% 0% 0% 0% 29% 18% 13% 4%

Traffic 5% 2% 4% 2% 0% 0% 2% 2% 8%

Hunting 5% 2% 1% 5% 0% 0% 0% 2% 6%

Other causes 0% 6% 14% 23% 0% 0% 22% 4% 2%

Total 10% 9% 19% 30% 0% 29% 42% 21% 20%

Table 4 Results of the Cox proportional hazards model

Effect/interaction Coef Exp (coef) Se (coef) z Pr (>|z|)

Presence of lynx −0.1595 0.8526 0.4201 −0.380 0.7042

Age 0.1260 1.1343 0.4150 0.304 0.7614

Severity of first winter 0.0002 1.0002 0.0051 0.041 0.9673

Sex 0.0592 1.0610 0.4527 0.131 0.8959

Presence of lynx:sex 1.7665 5.8503 0.5579 3.166 0.0015

Age:severity of first winter 0.0117 1.0117 0.0060 1.934 0.0531

Severity of first winter:sex −0.0099 0.9902 0.0060 −1.639 0.1013

Initially, all covariables and interactions were included in the model. The best model was then selected by choosing the one with the best Akaikeinformation criterion (AIC). Finally, only the four main effects and the interactions, presence of lynx:sex, age:severity of winter, and severity ofwinter:sex, were included in the model

R square00.076 (max possible00.811)

Likelihood ratio test033.2 on 7 df, p02.429e-05

Wald test037.61 on 7 df, p03.595e-06

Score (logrank) test043.45 on 7 df, p02.728e-07

n0420 (7 observations deleted due to missingness)

Eur J Wildl Res (2012) 58:567–578 573

Breitenmoser-Würsten 2008). We found a death rate of43% caused by lynx predation, which also represents ahigh proportion of the total mortality rate. These resultsindicate that the influence of lynx on its prey can differsignificantly and can be subject to a high degree ofvariance depending on the initial conditions.

Especially the density of the prey animals appears tohave an influence on the effects that lynx have on theirprey. In a highly dense (>20/km2) Roe Deer populationin Switzerland, lynx only killed 4% of the deer population(Liberek 1992, quoted in Breitenmoser and Breitenmoser-Würsten 2008). In a less dense Roe Deer population

Table 5 Refitted Cox model of period II with censoring of all Roe Deer that died because of hunting

Effect/interaction Coef Exp (coef) Se (coef) z Pr(>|z|)

Presence of lynx −0.745633 0.474434 0.325339 −2.292 0.021913

Age 0.487785 1.628704 0.319377 1.527 0.126686

Severity of first winter −0.002942 0.997062 0.003060 −0.961 0.336376

Sex −0.473230 0.622987 0.256581 −1.844 0.065129

Presence of lynx:sex 1.528979 4.613462 0.430551 3.551 0.000383

Age:severity of first winter 0.010578 1.010634 0.004753 2.226 0.026034

Initially, all covariables and interactions were included in the model. The best model was then selected by choosing the one with the best Akaikeinformation Ccriterion (AIC). Finally, only the four main effects and the interactions presence of lynx:sex and age:severity of winter were includedin the model

R square00.089 (max possible00.947)

Likelihood ratio test039.31 on 6 df, p06.21e-07

Wald test042.95 on 6 df, p01.193e-07

Score (logrank) test046.39 on 6 df, p02.473e-08

n0420 (7 observations deleted due to missingness)

Presence Of Lynxp < 0.001

1

yes no

Juvenilep = 0.013

2

yes no

Node 3 (n = 68)

0 500 1000 1500

0

0.2

0.4

0.6

0.8

1Node 4 (n = 140)

0 500 1000 1500

0

0.2

0.4

0.6

0.8

1Node 5 (n = 265)

0 500 1000 1500

0

0.2

0.4

0.6

0.8

1

Fig. 5 A conditional survivaltree used to split theobservations into distinctsubgroups with respect to theobserved survival times bymeans of cutpoints in thecovariates. The mostsignificance was found for thevariable lynx presence.Consequently, the data set isdifferentiated according to thisvariable. In the period when thelynx was present, survival ratesof the juveniles weresignificantly lower than those ofthe adults

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(2–5/km2) in eastern Poland, lynx were responsible forup to 37% of deer mortality (Jedrzejewski et al. 1993,Okarma et al. 1995, 1997). Similarly, in a less dense deerpopulation (0.5/km2) in Norway, lynx predation was respon-sible for the mortality of >50% of the radio-collared Roe Deer(Linnell et al. 1996). These observations can be attributed tothe highly efficient hunting and killing of deer by lynx even atvery low deer densities. This is confirmed by the functionalresponse of the animals, in which the killing rate increasessteadily until the Roe Deer density approaches 2/km2

(Nilsen et al. 2009a). Thereafter, the killing rate remainsconstant; the proportion of Roe Deer killed and theimpact on the population then decreases with increasingRoe Deer density (Nilsen et al. 2009a). The BavarianForest has a low Roe Deer density (1–5 animals/km2),and our results confirmed the prediction that the influence oflynx on the deer population is high when the deer occur atrelatively low densities. This is also in accordance with thefindings of Jedrzejewska and Jedrzejewski (2005), whoshowed in a long-term study that a stronger limitation bypredation occurs in less-productive environments. Also,results from a biogeographical scale have shown thatthe strength of density dependence in wild ungulatepopulations is low when large predators are present,particularly at northern latitudes with low primary productivity(Melis et al. 2009, Wang et al. 2009).

In our study, lynx were not present during the first studyperiod but were present during the second period, and thedeer survival rates were lower in the second period.However, the presence of lynx was not the only factorthat differed between the two study periods. Other factorsinclude alterations in habitat conditions, wildlife management,and climate.

Over the course of both study periods, the forest habitatchanged dramatically because of extensive bark beetle(I. typographus) infestation, which affected the dominantstands of spruce and led to the death of mature trees.This process results in profound ecological changes thatin turn lead to an increase in the quantity and quality ofbiomass available for consumption by herbivores (Heurichand Jehl 2000, Heurich and Neufanger 2005), and food supplyis a key factor in the dynamics of Roe Deer populations(Pettorelli et al. 2003; Kjellander et al., 2006). Also, thedevelopment of new ecotones and protective cover, causedby the death and collapse of mature trees and the growth ofearly successional stages, have positive influences on thehabitat for Roe Deer (Tixier and Duncan 1996, Gill et al.1996). Therefore, owing to these changes in the habitat, wewould expect higher survival rates of Roe Deer in the secondstudy period, but the opposite was true.

Another difference between the two study periods wasthe extended no-hunting zone and the reduced culling in thesecond study period. These factors should also have a

positive effect on the survival rate of Roe Deer, but thisfactor does not seem to have a notable influence on theobserved differences between the two study periods asthe results do not change remarkably when hunted RoeDeer are censored. While, on the whole, fewer Roe Deerwere killed by hunters during the second study period inthe National Park (an average of 30 vs. 56 in the firststudy period), the lower number is probably compensatedto some extent by the migration of more Roe Deer fromthe national park into adjacent hunting districts, wherethey were then shot. This assumption is supported by thefact that the percentage of collared deer killed by huntersduring the two study periods was similar.

Another factor that differed between the two studyperiods was winter feeding. At the beginning of the firststudy period, six Roe Deer feeding stations were maintained,and towards the end, three were maintained; during the secondstudy period, no feeding stations were kept. The feedingstations during the first study period could have contributedto a lower deer mortality. However, since the number offeeding stations was low (one per 23 km2), this influencemay have been negligible, especially if one considers thatthe collared deer were spread throughout the entire area andnot only in the vicinity of feeding stations. But whether winterfeeding is the reason for the found differences in survival ratecannot be determined statistically because there was a lineardependency between lynx occurrence and winter feeding. Ourresults indicated that it is likely that the presence of lynx is themost important factor leading to the observed differencesbetween the two study periods.

Roe Deer are highly susceptible to severe winters. Thetwo most important variables describing the severity ofwinter are the number of days with snow cover and theheight of the snow (Danilkin 1996). Owing to their smallbody size, Roe Deer have relatively high energy requirementsbut only low fat reserves. These characteristics are linked withtheir reproductive tactic of being income breeders (Andersenet al. 2000). They have difficulty moving about in snowbecause of their heavy foot load and low brisket height(Holand et al. 1998). Their mobility is even impaired by asnow depth of 20 to 40 cm, which occurs in milder winters inthe Bavarian Forest; on average, very severe winters arerecorded there every seven years (Fig. 1). The great influenceof severe winters on the density-independent mortality of RoeDeer populations has been shown in a number of studies (e.g.,Cederlund and Lindström 1983, Gaillard et al. 1993, Okarmaet al., 1995). As the results of this study indicate, winters arean important factor for Roe Deer mortality in the BavarianForest National Park, especially for young animals. This isdue not so much to the effect of temperature as it is tothe amount of snow. Grøtan et al. (2005) have shownthat continuous snow cover between October and Decemberin Norway greatly affects the Roe Deer population by

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extending the period with a negative energy balance.Danilkin (1996) reported a severe winter with snowdepths of 1 to 1.5 m starting at the end of October ineastern Russia in which numerous groups of 20 to 30individuals died of starvation. By the end of the winter,the population had been reduced to 25–33% of the autumnpopulation. In northern Europe, starvation as a result ofsevere winters is the greatest natural cause of death. InSweden, this can amount to 40% of the population(Cederlund and Lindström 1983). In Central Europe,severe winters can also have marked effects. Examplesare the winters of 1969/70, 1976/77, and 1978/79, duringwhich approximately 33% of the animals in Poland died;the losses were especially high for fawns (77–90%) andold individuals (Fruzinski and Labudzki, 1982, Kaluzinski1982). The result of our study, with the documentedinteraction between the severity of the first winter andthe mortality of fawns in the Bavarian Forest NationalPark, confirm these observations.

Severe winters actually have a dual effect on Roe Deer.As discussed above, the deer are directly affected by theweather conditions, but they are also indirectly affectedthrough their increased risk of falling victim to predators.Their Roe Deer heavy foot load causes them to sink into thesnow, thereby inhibiting their movement considerably,whereas their predators—especially lynx—are well adaptedto moving in snow (Holand et al. 1998). Danilkin (1996)observes that severe winters in combination with predatorshave a negative effect on Roe Deer populations. Melis et al.(2009) confirmed this observation and also conclude that themortality rates caused by winter and large predators arenot compensatory. In contrast, we found no effect of theinteraction between winter severity and lynx presence.One reason for this might be the migratory behaviourof Roe Deer in our study area. Most of the animalsmigrate in winter to the valleys, where the snow depthis much lower and the movement of the animals is not asrestricted. Also, Roe Deer tend to congregate near feedingstations and human settlements in winter (Mysterud et al.1997, Bunnefeld et al. 2006). Although such areas could besystematically targeted by lynx, the larger groups of animals atthese feeding stations might lead to the lynx being spottedearlier, giving the deer more time to escape its attack.

Various investigations have indicated that the sex ratioof fawns is balanced because of similar fawn survivalrates of the sexes (Andersen et al. 1995, Gaillard et al1997). However, it has also been found that for does ingood physical condition, the sex ratio of fawns tendstoward more females, while for does in poor physicalcondition, the ratio tends toward more males (Hewisonand Gaillard 1996, Hewison et al. 1999). Among theadults, the lower survival rate of bucks results in asurplus of females (Ratcliffe and Rowe 1985, Cobben

et al. 2009). Reasons for this may be the aggressivenessof territorial fighting, which can result in serious injuriesor possibly even death, or increased mortality as a resultof migration, which especially takes place with increasingpopulation pressure (Gaillard et al. 1993). It is expected thatlynx do not selectively hunt male or female Roe Deer and thatmale and female Roe Deer are hunted with equal success inproportion to their respective abundance in the population(Breitenmoser and Breitenmoser-Würten 2008, Andersen etal. 2007). Therefore, it is expected that the occurrence of lynxshould not change the sex ratio. According to that, our resultsshowed a lower survival of bucks in the period when lynx waspresent.

We observed a mortality of juveniles and adult Roe Deerin the study area, especially during a severe winter andduring the second study period when lynx was present.However, the differences were lower than reported in otherinvestigations because our fawns not fitted with transmittersuntil after the age of 6 months; younger fawns were consid-ered in other studies, and the fawn mortality is generallyvery high during the first summer (Gaillard et al. 1997). Inaddition, we classified juveniles as fawns and yearlings, andthe annual yearling survival is usually close to the maximumsurvival of prime age Roe Deer, which lies between 0.74and 0.88 (Gaillard et al. 1998).

Conclusion

Under the prevailing conditions in the study area, thesurvival rates of adult Roe Deer were low than reportedfor other parts of Europe. In spite of the considerableimprovement of Roe Deer habitat caused by bark beetleinfestation, the combination of severe winters and predationby lynx markedly decreased the survival of Roe Deer in theBavarian Forest National Park. The study of Wilmer et al.(2007) suggests that the dynamics of predator–prey systemsshould be stabilized by ambush or stalking predators. In thisway, the mortality of prime-aged prey increases, therebylengthening the extent of the predator pit and decreasingthe likelihood of prey irruption. The observed effects oflynx and winter severity should be considered in thedevelopment of future Roe Deer management plans inthe Bavarian Forest National Park. In particular, it maybe possible to reduce the control of Roe Deer in thenational park even further, thereby contributing to thefulfilment of the park's hands-off policy.

Acknowledgements This study is part of a project on the predator–prey relationship of Eurasian Lynx, Red Deer, and Roe Deer carriedout by the Bavarian Forest National Park Administration, Departmentof Research and Documentation. GPS collaring and behaviouralobservations complied with German laws. Financial support wasprovided by the EU Programme INTERREG IV (EFRE Ziel 3), T-mobile,

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and the Bavarian Forest National Park Administration. We kindly thankHorst Burghart, Martin Gahbauer, Helmut Penn, Michael Penn, RüdigerFischer, and Lothar Ertl for technical support. We also thank Karen A.Brune for language editing.

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