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Where have all the young wolves gone? Traffic and cryptic mortality create a wolf population sink in Denmark and northernmost Germany

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Conservation Letters
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Large carnivores are currently recolonizing Europe following legal protection, but increased mortality in landscapes highly impacted by humans may limit further population expansion. We analyzed mortality and disappearance rates of 35 wolves (of which three emigrated, nine died and 14 disappeared by 1 January 2020) by genetic monitoring in the heavily cultivated and densely populated Jutland peninsula (Denmark and Schleswig‐Holstein, Germany). Annual traffic kill rate estimates ranged from 0.37 (95% CI: 0.11–0.85) to 0.78 (0.51–0.96) in the German part, equivalent to 0.08 (0.02–0.29)–0.25 (0.13–0.46) for the entire region, in the absence of any registered Danish roadkills. In Denmark, annual mortality rate estimates ranged from 0.46 (0.29–0.67) to 0.52 (0.35–0.71), predominantly from cryptic mortality. Despite successful reproductions, we conclude the region is a wolf population sink, primarily driven by cryptic mortality, most likely illegal killing. We hypothesize that frequent encounters between wolves and wolf‐averse persecutors in cultivated landscapes may cause unsustainably high mortality rates despite the majority of hunters respecting protection laws.
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Received: July  Revised:  January  Accepted:  April 
DOI: ./conl.
LETTER
Where have all the young wolves gone? Traffic and cryptic
mortality create a wolf population sink in Denmark and
northernmost Germany
Peter Sunde1Sebastian Collet2Carsten Nowak3Philip Francis Thomsen4
Michael Møller Hansen5Björn Schulz6Jens Matzen7Frank-Uwe Michler8
Christina Vedel-Smith9Kent Olsen9
Department of Bioscience, Aarhus University, Rønde, Denmark
Senckenberg Research Institute and Natural History Museum Frankfurt, Conservation Genetics Section, Gelnhausen, Germany
Senckenberg Research Institute and Natural History Museum Frankfurt, Conservation Genetics Section, Gelnhausen, Germany
Department of Biology, Aarhus University, Aarhus C, Denmark
Department of Biology, Aarhus University, Aarhus C, Denmark
Stiftung Naturschutz Schleswig-Holstein, Molfsee, Germany
Stiftung Wildtiere im Norden, Molfsee, Germany
Faculty of Forest and Environment, Eberswalde University for Sustainable Development, Eberswalde, Germany
Natural History Museum Aarhus, Aarhus C, Denmark
Correspondence
Peter Sunde, Department of Bioscience,
Aarhus University,Grenåvej , 
Rønde, Denmark.
Email: psu@bios.au.dk
Abstract
Large carnivores are currently recolonizing Europe following legal protection,
but increased mortality in landscapes highly impacted by humans may limit fur-
ther population expansion. We analyzed mortality and disappearance rates of 
wolves (of which three emigrated, nine died and  disappeared by January
) by genetic monitoring in the heavily cultivated and densely populated Jut-
land peninsula (Denmark and Schleswig-Holstein, Germany). Annual traffic kill
rate estimates ranged from . (% CI: .–.) to . (.–.) in the Ger-
man part, equivalent to . (.–.)–. (.–.) for the entire region,
in the absence of any registered Danish roadkills. In Denmark, annual mortal-
ity rate estimates ranged from . (.–.) to . (.–.), predominantly
from cryptic mortality. Despite successful reproductions, we conclude the region
is a wolf population sink, primarily driven by cryptic mortality, most likely ille-
gal killing. We hypothesize that frequent encounters between wolves and wolf-
averse persecutors in cultivated landscapes may cause unsustainably high mor-
tality rates despite the majority of hunters respecting protection laws.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the
original work is properly cited.
©  The Authors. Conservation Letters published by Wiley Periodicals LLC
Conservation Letters. ;:e. wileyonlinelibrary.com/journal/conl 1of10
https://doi.org/./conl.
2of10 SUNDE  .
KEYWORDS
Canis lupus, Denmark, genetic wildlife monitoring, Germany, human–wildlife conflict, illegal
killings, large carnivores, poaching, recolonization, roadkills, source–sink
1 INTRODUCTION
European large carnivore populations have rebounded fol-
lowing implementation of legal protection (Chapron et al.,
); for example, wolves (Canis lupus L.) in Germany
rapidly expanded from one pack in  to  in 
(Reinhardt et al., ), providing evidence for the effec-
tiveness of legislation to restore populations. Behavioral
flexibility and adaptability have enabled wolves to exploit
habitats highly impacted by humans (Mech, ). How-
ever, human-induced mortality rates, a major cause of
population regulation among large carnivores in habitats
shared with humans (Chapron et al., ), may limit the
future population expansion and ultimate distribution of
wolves in the predominantly anthropogenic landscapes of
Europe. Where wolves enjoy legal protection, traffic acci-
dents and illegal killing contribute the majority of human-
induced mortality. Where such anthropogenic mortality
rates exceed reproductive success, the population of the
habitats sinks, ultimately draining regional populations of
individuals and inhibiting establishment in otherwise suit-
able habitats (Fahrig & Rytwinski, ; Recio et al., ).
Illegal killing of large carnivores occurs globally, including
inGermanyandDenmark(Heurichetal.,; Reinhardt
et al., ; Sonne et al., ), and may regulate wolf popu-
lations locally or regionally (Liberg et al., ; Suutarinen
& Kojola, ;Trevesetal.,). Sociopolitical factors
driving the illegal killing of wolves are complex (Chapron
&Treves,; Liberg et al., ; Suutarinen & Kojola,
; von Essen et al., ; von Essen et al., )asare
their interactions with landscape conditions. For example,
in Finland, rates of illegal killing among breeding GPS-
collared wolves positively correlated with the frequency
with which they crossed roads and hence be accessible to
poachers (Suutarinen & Kojola, ). In Germany, sur-
vival of territorial wolves were higher inside military train-
ing areas, apparently because of reduced exposure to per-
secutors (Reinhardt et al., ). However, the extent to
which wolf mortality in densely populated and cultivated
landscapes of Western Europe exceeds the species’ repro-
ductive capabilities have remained unquantified.
Here, we analyze verified and apparent wolf mortal-
ity rates on the Jutland peninsula (, km)inDen-
mark and Schleswig-Holstein, Germany, an intensively
cultivated region, where individual wolves are intensively
monitored and emigration is limited, which has received
a steady flow of wolf immigrants from the Central Euro-
pean source population. Wolf population dynamics in this
region may thus exemplify the situation in other parts of
West and Central Europe where fates of individuals are less
easy to monitor.
2 MATERIALS AND METHODS
2.1 Study area
Schleswig-Holstein with Hamburg (SH; , km,.
million people,  km: % developed, % farmland,
% forest) and the Danish part of Jutland (DK; , km,
. million people,  km: % developed, % farm-
land, % forest, % heathland) constitute the -km long
Jutland peninsula (Figure ). Jutland is connected to the
Central European mainland (CE) by a -km wide stretch
of land between Hamburg (. million people) and the
Baltic Sea. Most of its human population resides in the
southern district of SH that borders on Niedersachsen and
Mecklenburg-Vorpommern.
2.2 Wolf monitoring in Germany and
Denmark
Wolves in Germany and Denmark belong to the Central
European Lowland population (Andersen et al., )
centered in Western Poland and Eastern Germany,
with single breeding pairs in Denmark, The Nether-
lands, Belgium, and Czech Republic. These coun-
tries monitor the population genetically based on 
microsatellite markers using joint standards agreed by
the CEWolf consortium (www.senckenberg.de/CEwolf),
enabling genotyped individuals to be tracked through-
out the entire population area (for further details, see
Appendix S).
In DK and SH, governmental agencies systematically
sample DNA from scats, dead wolves, and wolf-killed live-
stock. In SH (where sheep farming is widespread and
until recently not adapted to wolf presence), livestock
killings have contributed with most genotype identifica-
tions. In DK, wolves kill livestock less frequently, so moni-
toring is primarily undertaken by DNA retrieval from scats
(obtained by active search) (Appendix S).
SUNDE  . 3of10
FIGURE 1 Map of the Jutland peninsula, with verified (C) observations of genotyped wolves,  to January , . The last known
observation in the region of each individual before January ,  is indicated by fate (a cross outside the region indicates the location of
death of a wolf that emigrated out of the region is also shown on the map)
4of10 SUNDE  .
We also included GPS data from a vagrant male wolf
(GWm) that immigrated to SH from Sachsen-Anhalt
in April , remaining there for weeks before emi-
grating through Mecklenburg-Vorpommern to Poland
(Appendix S).
2.3 Estimation of observation
frequencies and probability of local
persistence
We created two georeferenced observation datasets of iden-
tified individuals from the wolf registration databases in
DK and SH, respectively, as of April , . The first
dataset (A: rigorous) consisted of full genotype profile
identifications. The second data set (B: pragmatic) also
included verified wolf observations that could be assigned
with a high level of confidence to an individual of known
genotype (e.g., photo documentation or incomplete DNA
profiles). Incomplete DNA profiles were accepted when
based upon a minimum of nine loci with amplifications
of a heterozygote and amplifications of a homozygote
locus or where individual assignment could be attained
with high probably due to multiple sampling of an indi-
vidual within a highly restricted temporal and geographic
context (Appendix S).
We estimated an individual’s daily observation prob-
ability as rday =(n–)/x, where nis the number of
observation days and xis the number of days between
the first and last observation. Hence, if an individual was
registered on  different dates over a -day period,
rday =( )/ =. day.
From rday, we derived the probability that a wolf would
not be detected within a time period of zdays since its last
observation ( rz)as(–rday )z. Individuals that had an
( rz)<. were scored as disappeared. We estimated
the probable date of disappearance as the last date of obser-
vation +the mean number of days between consecutive
observations before it disappeared. At the population level,
we modeled rday and the mean number of days between
consecutive observations (/rday) an interactive function
of country (SH or DK) and year as fixed effects with wolf
identity as random effect (Appendix S). If a wolf was only
observed once, its disappearance date was estimated by
adding the population mean observation interval in the
country and the year it was observed to the date of the last
observation.
2.4 Mortality analysis
We analyzed cause-specific mortality and/or disappear-
ance rates as the number of verified deaths and/or
disappearance events per exposure day. We esti-
mated cause-specific death and disappearance rates
as (i) traffic, (ii) disappearances +verified ille-
gal killings, and (iii) total (all verified deaths +
disappearances).
An individual’s exposure period started when its genetic
profile was initially registered in the region and lasted until
it was verified as dead or emigrated, estimated to have dis-
appeared, or to January ,  if alive in the region by that
date (Figure ). In April , we made a final check of our
databases to confirm that no wolves categorized as disap-
peared had reappeared (last DNA-profile sampled Febru-
ary , ). Wolves born in the region entered the analy-
sis on the first date their genetic profile was detected after
November in the year they were born. For wolves mov-
ing between DK and SH, we divided the exposure days for
observation intervals involving border crossings between
DK and SH relative to the ratio between mean observation
frequencies in the two states, hence allocating the major-
ity of the exposure days for trans-boundary intervals to DK
(Table ).
For the entire SH–DK region as well as for SH and DK
individually, we estimated cause-specific event rates after
three different data selection criteria. Using the first, most
rigorous method (method ), individual exposure inter-
vals were calculated from data set A (strictly DNA-verified
observations). Disappearance events were allocated to DK
or SH depending on where the wolf was last observed. Indi-
viduals registered dead as the first record did not enter
the analysis. Using the second, more pragmatic method
(method ), we calculated individual exposure intervals
from data set B (including probable identifications). Since
most immigrants to SH from CE dispersed further into DK
within few weeks (Figure ) and mean observation inter-
vals in DK before  were substantially longer than in
SH(andlateroninDK;Table), three disappeared indi-
viduals last observed in SH, – (Figure )were
treated as emigrated to DK and disappeared there. Other
criteria were similar to method . Method was simi-
lar to method , but included five individuals reported
killed by cars as their only registration. While we accept
that inclusion of individuals killed at their first registra-
tion is not analytically rigorous (because they are drawn
from an unknown population of undetected individuals),
we consider that it is justified in this case, as they rep-
resented the majority of traffic deaths and probably rep-
resented individuals killed shortly after entering SH from
CE. To compensate for exposure time before registration,
we arbitrarily added  exposure days to each roadkill
not previously registered in the SH–DK region, which was
six times the mean observation interval in SH in 
(Table ).
SUNDE  . 5of10
FIGURE 2 Observation timelines of the  genotyped wolves registered in Schleswig-Holstein and Denmark, –. Data obtained
after January ,  was not included in the mortality analysis, hence indicated with gray shaded background. Accordingly, GWm and
GWf (estimated disappeared c. January ,  and July ,  by method ) was coded as alive in the analysis. Multiple possible birth
dates of GWm are the breeding seasons when it could potentially have been born based on pedigree analysis in relation to its parents (it is
most likely it was born in the last of these years)
TABLE 1 Mean observation intervals for wolves in Denmark (DK) and Schleswig-Holstein (SH), as predicted from Generalized Linear
Mixed models (observation unit =observation intervals, response variable: /length [days] of the observation interval; link =logit; binomially
distributed errors with variance inflation factors differentiated to state and period [– vs. –])
DNA-verified observations All observations
Mean observation intervals (days) 1 ryear (%) Mean observation intervals (days) 1 ryear (%)
Year DK (95%CL) SH (95%CL) DK:SH DK (95%CL) DK (95%CL) SH (95%CL) DK:SH DK (95%CL)
  (–)  (–) .  (–)  (–)  (–) . (–)
  (–)  (–) .  (–)  (–)  (–) . (–)
  (–)  (–) .  (–)  (–)  (–) . . (–)
  (–) () . (–)  (–)  (–) . . (–.)
  (–) (–) . . (–)  (–) (–) . (–.)
  (–) () . . (–)  (–) () . (–)
  (–) (–) . . (–.)  (–) (–) . (–)
  (–) () . . (–.)  (–) () . (–)
DK:SH indicate the ratio between mean observation lengths in DK and SH. ( ryear) is the estimated percentage probability that a wolf will escape detection for
 days (only shown for DK as all estimates for SH were <. %).
6of10 SUNDE  .
3RESULTS
3.1 Observation patterns
By January , ,  different wolves had been identified
through genotyping in SH and DK,  immigrants from CE
andborninDK(Figure). Nine of the immigrants were
first registered in SH and then in DK, two only in DK, and
 only in SH (six killed, four disappeared, one returned
to CE). Thirteen of  wolves known to have entered SH
from independent data (nine of  immigrants registered in
DK, three Danish-born wolves registered in CE, and one
GPS-tagged individual; Figure ) were registered geneti-
cally in SH, equating to a detection probability of . (%
CI: .–.).
On average, immigrants from CE stayed for  days
(SE =.) in SH before leaving SH again (Kaplan–Meier
analysis with  emigrations as events, one death, and four
disappearances as censored cases, stay lengths estimated
using method ). Immigrants from DK on average stayed
for  days (SE =) in SH before dispersing to CE or
returning to DK. No immigrants to DK left the country
upon entry (Figure ).
From  to , the mean interval between consecu-
tive genetic identifications in SH and DK reduced from 
to and from  to  days, respectively (Table ).
3.2 Cause-specific mortality and
disappearance rates
As of January , , of the  genotyped wolves, repre-
senting .. exposure years (% in DK, % in SH),
nine were alive, nine were registered dead (seven traffic
kills, one diseased, one shot illegally), three emigrated, and
 had disappeared (Table ).
All traffic deaths were registered in SH (Table ).
Depending on estimation method, annual road fatality
rates ranged from . to . for SH and from . to .
for the entire SH–DK region (Table ).
In DK, the annual rate of illegal killings and disappear-
ances ranged from . to . and the total death +dis-
appearance rate from . to . (Table ). For SH, total
annual rates of deaths +disappearances varied from .
to ., with traffic deaths representing the most frequent
event type and the only type of verified death (Table ).
4DISCUSSION
With an % registration probability of wolves passing
through SH and a mean observation frequency of less than
weeks, it is unlikely that a wolf in SH would avoid detec-
tion for more than a few months. The same also applies
for DK since –, when the Danish wolf survey was
established. Most immigrants from CE were transient in
SH and moved on to DK from where they never returned. It
should therefore be safe to conclude that all, or at least the
vast majority, of wolves that disappeared in DK also died
there. It is not possible to draw the same conclusion for
SH, as wolves last observed in SH might have dispersed to
DK or CE. At least one genetically unidentified wolf lived
in DK during – (Sunde & Olsen, ), so at least
one and possibly all three wolves that disappeared from
SH during – potentially dispersed to DK and eventu-
ally died without ever being genotyped there. With respect
to estimation of disappearance rates, method is therefore
conservative for DK and possibly inflated for SH, whereas
method might give a more accurate estimate for both DK
and SH. Method (which also included wolves registered
first when killed by cars) was less rigorous, as an unknown
number of wolves might have entered the urbanized south-
ern part of SH and returned to CE without entering the
analysis. It may nevertheless be realistic, as a total regis-
tration rate of % and >% registration probability within
weeks indicate that the wolves not registered before they
were killed had died few days after entering the urbanized
southern part of SH from CE. Further support for using
this method comes from the fact that despite our arbitrary
setting of the number of exposure days of wolves killed at
initial registration to  days (six times the mean observa-
tion interval in , so unrealistically high), the  expo-
sure days from the five cases comprised less than % of the
total number of exposure days in the analysis for SH and
less than % for SH +DK. Hence, the arbitrarily chosen
number of exposure days per wolf killed at first encounter
had little influence on mortality estimates generated
from method compared with the contribution of death
events.
The most conservative estimates of annual mortality
rates in both SH (traffic: .) and DK (deaths and disap-
pearances: .) exceeded natural and traffic-caused mor-
tality rates in Sweden (–.: Liberg et al., ) and Fin-
land (natural: ., traffic: <.: Suutarinen & Kojola,
). They also exceeded the maximum sustainable har-
vest rates (.) and total sustainable mortality rates
(.) estimated for wolf populations (Adams et al., ;
Fuller et al., ), suggesting that the Jutland peninsula
constitutes a population sink.
Even though the traffic fatality rates exceeded sus-
tainable harvest rates in SH, traffic mortality was not a
population-regulating factor for the whole region, as no
traffic deaths were registered in DK. The locations of
the traffic kills (Figure ) reveal that most traffic deaths
occurred in a delimited “death zone” around Hamburg,
affecting wolves that dispersed through the area. This
SUNDE  . 7of10
TABLE 2 Number of genotyped wolves registered in Schleswig-Holstein (SH) and Denmark (DK) by January , showing the cumulative number of exposure days and cause-specific
event rates
Number of wolves according to fate categories as of
January 1, 2020 Cause specific event rate per year (95% CI)
Region Method A E N I T D Total Days Traffic deaths Illegal +disappeared Deaths +disappeared
SH    . (.–.) . (.–.) . (.–.)
a   . (.–.) . (.–.) . (.–.)

a   . (.–.) . (.–.)
DK   . (.–.b). (.–.) . (.–.)

a  . (.–.b) . (.–.) . (.–.)
DK +SH    . (.–.) . (.–.) . (.–.)
   . (.–.) . (.–.) . (.–.)
   . (.–.) . (.–.)
Fates by January , : A =alive, E =emigrated from region, N =natural death cause, I =illegal killing, T =traffic kill, D =disappeared.
Methods: : observations based only on full DNA-profiles; : observations of likely identifications included; : wolves killed by cars as the first ever registration in the region included, associated with  exposure days
each (see text for full explanation).
aIncludes three individuals last observed in SH (-), presumed emigrated to DK and one individual (GWm) coded as emigrated to DK on  December  based on a likely identification (therefore coded as
aliveinSHbymethod,butasaliveinDKandemigratedfromSHbymethod).
bUpper confidence limit calculated by substituting events/xdays with event/(x)days.
8of10 SUNDE  .
emphasizes the potential importance of local areas with
heavy traffic as regional population drains.
The reasons for the apparently unsustainably high mor-
tality rate in DK are more subtle, as disappearances and
one illegal killing accounted for nine of  presumed
deaths (based on the most conservative estimate). The
annual rate of DK disappearances and illegal killings (most
conservative estimate: .) exceeds the highest measured
rates in Sweden (.) (Liberg et al., ) and equals the
highest rates measured in Finland (.–.) (Suutarinen
& Kojola, ), levels which, in both countries, resulted in
population declines. Unreported car accidents are unlikely
to contribute significantly to the high disappearance rates
since most wolves disappeared from areas with relatively
low traffic intensity (Figure ) and because most motorists
are aware of, and report, hitting a wolf. Eliminating all
other explanations, illegal killing remains the only plau-
sible reason behind most DK disappearances.
That illegal killing is the predominant cause of high wolf
disappearance rates is not unexpected, given that accep-
tance of illegal killing to resolve wolf conflicts seem to be
widespread amongst rural Jutland landowners (Højberg
et al., ).
The results from the Jutland peninsula contrast else-
where in Germany where the population increased by
% yearduring – (Reinhardt et al., ). Dif-
fering patterns of landscape and landownership, rather
than attitudes, potentially explain this difference. Relative
to the East-Central Germany and Western Poland source
population area, forest areas in SH and DK are small, frag-
mented, and usually managed by multiple landowners.
Accordingly, wolves in SH and DK may move between
more properties, exposing themselves to greater numbers
of potential persecutors than do wolves in the core pop-
ulation. Wolves establishing territories in German mili-
tary training areas survived better than wolves in similar
habitats outside the training areas (Reinhardt et al., )
implying that illegal killing are conditional on landowner-
ship and that hunting practice is also a population regu-
lating factor elsewhere. If this is the case, the future dis-
tribution and abundance of European wolves may rather
be more defined by (illegal) mortality driven source–sink
dynamics than by habitat availability per se, as previously
described for the Eurasian lynx (Lynx lynx) in Germany
and the Czech Republic (Heurich et al., ).
We therefore suggest that such killings arise from ran-
dom encounters between wolves and people willing and
able to kill wolves when the opportunity occurs. Such
illegal killing fundamentally differs from the common
practice in the continuous forest landscapes in Fennoscan-
dia where wolves are actively hunted through organized,
communal efforts under snow-covered conditions (Suu-
tarinen & Kojola, ). In Denmark, hunting is practiced
on >% of the rural land surface (Primdahl et al., ).
As a result, illegal killing on small estates is probably more
feasible, “private,” and less subject to social control than
that in Fennoscandia. In this situation, proportionally few
active individuals could inflict unsustainably higher kill
rates there compared with Fennoscandia, where the num-
ber of separate ownerships encompassed within a wolf’s
activity range is low. If this explanation is true, local poach-
ing rates should inversely correlate with mean estate size
and be highest among the most mobile individuals, such as
dispersing vagrants. In that case, the availability and spa-
tial distribution of wolf habitats with low poaching risk of
sufficient size to include breeding home ranges may be of
crucial importance for regional persistence of wolves (see
also Grilo et al., ). Ultimately, improved understand-
ing of landscape-related mortality rates and the sociopolit-
ical drivers causing violations to protective legislation are
a prerequisite to predict better wolf colonization success in
the densely populated landscapes of West-Central Europe.
In western countries, illegal carnivore persecution
appears rooted in resource conflicts (game, livestock),
committed in frustration with, or as acts of political resis-
tance against, governmental policies (Liberg et al., ;
Pohja-Mykra & Kurki, ; von Essen et al., ;von
Essen et al., ). Therefore, mitigation initiatives are
essential to increased acceptance of protective legislation
to avoid illegal actions determining where wolf popula-
tions can and cannot become established in the future
(Pohja-Mykrä, ; Sonne et al., ;Treves&Bruskot-
ter, ).
ACKNOWLEDGMENTS
We are grateful to the many dedicated and hardwork-
ing volunteers in Germany and Denmark who assisted
with the practical wolf monitoring and to T.S. Jensen and
L.W. Andersen for pioneering wolf monitoring in Den-
mark. A.D. Fox kindly polished the language and provided
thoughtful comments that strongly improved the final ver-
sion of the manuscript.
AUTHORS’ CONTRIBUTIONS
P.S. analyzed the data and led the writing of the paper.
J.M. and B.S. were coordinating and conductingwolf mon-
itoring in Schleswig-Holstein; K.O., C.S.V., and P.S. were
responsible for the monitoring in Denmark. C.N. and S.C.
were responsible for genetic analyses of samples from Ger-
many and partly from Denmark and organized the register
of genotyped wolves in Central Europe. M.M.H. and P.F.T.
were responsible for genetic analyses in Denmark since
. F.W. provided GPS data on GWm. All authors
provided input to the manuscript and its revised version.
SUNDE  . 9of10
ETHICS STATEMENT
The search for and sampling of genetic material from
wolves involved nonintrusive methods that did not affect
the sampled subjects. Active monitoring efforts at all times
followed the stringent procedures and obligations imposed
by the states’ laws and regulations for activities on pub-
lic and private land. The capture, handling, and GPS tag-
ging of wolf GWm was licensed by the federal state
of Sachsen-Anhalt (animal welfare permit: --
HNEE, permit for tagging wild specially protected animals:
WZI  ).
DATA ACCESSIBILITY STATEMENT
The data that support the findings of this study are openly
available at http://doi.org/./RG....
CONFLICT OF INTEREST
The authors declare no conflicts of interest
ORCID
Peter Sunde https://orcid.org/---X
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SUPPORTING INFORMATION
Additional supporting information may be found online
in the Supporting Information section at the end of the
article.
How to cite this article: SundeP,ColletS,
Nowak C, et al. Where have all the young wolves
gone? traffic and cryptic mortality create a wolf
population sink in Denmark and northernmost
Germany. Conservation Letters.;14:e.
https://doi.org/./conl.
... So far, legal protection of the population after the European Habitats Directive and changes in human attitudes have favoured the wolf comeback to many regions Ciucci 2009, Cimatti et al. 2021), including densely populated areas like Germany , Jarausch et al. 2021. Despite the risks that the species face in many areas, such as poaching and traffic collisions (Liberg et al. 2012, Sunde et al. 2021, wolves found patches of available habitat and managed to spread and increase their numbers not only in Germany but also to neighbouring areas in Denmark and the Netherlands (Large Carnivore Initiative for Europe 2022). This quick recovery shows the flexibility of the species and its ability to recover even in landscapes with intensive human use (López-Bao et al. 2015). ...
... It is possible that the arrival of the wolf in a previously unoccupied landscape with high prey densities (Carpio et al. 2021) and effective legal protection created an ideal combination for the species to thrive. In addition, the high survival values might indicate that the rates of undetected illegal persecution and other human-caused mortality in Germany are so far rather low compared to other regions in Europe (Liberg et al. 2012, Sunde et al. 2021. The official German record of detected illegal kills are given as approx. ...
... In Denmark, on the other hand, annual survival rates range between 0.48-0.54 (Sunde et al. 2021), and the Danish wolf population only survives because it is supported by dispersing animals from Germany. In comparison, the mean survival probability across all age classes of the German wolf population is 0.81. ...
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Demographic parameters are key to understanding population dynamics. Here, we analyse the survival and reproduction of the German wolf population in the 20 years following recolonization. Specifically, we analysed the effects of environmental, ecological and individual characteristics on 1) survival probability of the population; 2) annual survival rates of age classes; 3) reproduction probability; and 4) reproductive output, measured as the number of detected pups/juveniles. Using Cox proportional hazards model, we estimated a median survival time of circa three years for wolves. Annual survival probabilities were found to be 0.75 for juveniles, 0.75 for subadults and 0.88 for adults. Survival was lower for juveniles in winter and for subadult males in summer, probably associated with dispersal events. Low habitat suitability was clearly associated with lower survival in juveniles and subadults, but not in adults. Local territory density was related to increased survival. Reproduction probability within a territory was 0.88, but explanatory variables had no effect. Reproductive output was four pups/juveniles on average, positively related to habitat suitability and female experience, but negatively related to territory density. Survival values were very high for the species when compared to other regions. We hypothesize that carrying capacity has not been reached in the study area, thus the survival may decrease in the future if the landscape becomes saturated. Furthermore, our results highlight a spatial pattern in survival and reproduction, with area of better habitat suitability favouring faster population growth. Thus, targeting conservation measures to low habitat suitability areas will have a strong population effect on the short term by boosting survival and reproduction of the individuals, while long‐term viability should be carefully planned with high suitability areas in mind, as those contain the territories with higher survival and reproduction potential.
... Nevertheless, conservation of wolves might have lower public support than that of other large carnivores (Trajçe et al., 2019). Previous analyses have also suggested that illegal killing could have considerable influence over wolf population numbers and trajectories (Liberg et al., 2020;Sunde et al., 2021). Moreover, insufficient data-and data standardization-still limit research and broad-scale analysis (Lino et al., 2022). ...
... In June 2020, genetic samples were collected with swabs on two livestock kills near Reit/Kössen in Bavaria, Germany ( Figure 1). The samples were analyzed with 14 microsatellite markers, and sequencing of the mitochondrial control region as routinely done in the monitoring of wolves in Germany and other countries included in the CEwolf consortium Sunde et al., 2021) and identified as an individual male wolf (GW1706m). Analysis of ancestry-informative SNPs to detect possible wolf-dog hybrids (Harmoinen et al., 2021) Extracted DNA from wolf GW1706m was sent to Slovenia, for comparison with reference samples from this country, with the aim of determining his pack of origin, following the approach of Andersen et al. (2015). ...
... Although the wolves are recovering in range and numbers in many areas (e.g., Jarausch et al., 2021;Marucco et al., 2022;Szewczyk et al., 2019), isolated and small populations can also go extinct, as seen in the Sierra Morena wolf population in southern Spain (Boitani et al., 2022;G omez-S anchez et al., 2018). Other threats to wolves in humandominated landscapes include poaching (Sunde et al., 2021) and poisoning (Musto et al., 2024). Infectious diseases such as canine distemper virus can cause high mortality in small populations (Turner et al., 2023), where more abundant species could act as disease reservoirs (Beineke et al., 2015). ...
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Large carnivores such as wolves (Canis lupus) at times disperse distances of several hundred kilometers, which may enable gene flow over vast distances. Such long‐distance dispersal events, however, often remain undetected, and documenting long‐distance dispersers and their movements typically depend on strong transboundary collaborations. Here, we report the dispersal of a wolf (MSV0FF) from the Alpine region of northern Slovenia to Bavaria in southern Germany, a straight‐line distance of around 300 km. The disperser originated in a pack with a genetically diverse breeding pair, where the father exhibited ancestry from the Dinaric and Italian Alpine populations. Genetic analysis of the mother indicated that she was an immigrant from a divergent population further south in the Dinaric‐Balkan region. Such a varied ancestry augments the probability of immigrants being genetically misclassified as wolf‐dog hybrids in their area of arrival, which increases the risk of unfavorable management decisions toward individuals that would be genetically highly valuable for the recipient population. Wolf MSV0FF therefore demonstrates the benefits of international collaborative monitoring networks and the value of sharing samples and analytical approaches for the monitoring of wide‐ranging species.
... Our estimate based on monitoring reports and expert assessments in 34 countries (S1 Appendix) reveals that by 2022 at least 21,500 wolves inhabit Europe, 19,000 of which are found in the European Union (EU) [8], an increase of 58% from the 12,000 estimated 10 years ago [2]. In the EU, wolves share the landscape with millions of wild ungulates [4], 279 million head of livestock and 449 million people [9,10]. ...
... However, it is worth noting the recent nation-wide estimate in Italy based on state-of-the-art methods combining systematic field surveys and integrated population modeling [18] that demonstrated the application of robust statistical methods across large scales. Some countries have very detailed monitoring, where almost every individual wolf is known and the genetic pedigree of the population is available (Denmark [19], Finland [20], Germany [21], the Italian Alps [22] and Scandinavia [23-25]). Genetic monitoring methods are diverse and serve a variety of goals: assignment of individuals to source populations, population size estimation, determining genome-wide inbreeding and diversity or detecting hybridization with other canids [26-28]. ...
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The recovery of wolves (Canis lupus) across Europe is a notable conservation success in a region with extensive human alteration of landscapes and high human population densities. We provide a comprehensive update on wolf populations in Europe, estimated at over 21,500 individuals by 2022, representing a 58% increase over the past decade. Despite the challenges of high human densities and significant land use for agriculture, industry, and urbanization, wolves have demonstrated remarkable adaptability and increasing population trends in most European countries. Improved monitoring techniques, although varying in quality and scope, have played a crucial role in tracking this recovery. Annually, wolves kill approximately 56,000 domestic animals in the EU, a risk unevenly distributed and differently handled across regions. Damage compensation costs 17 million EUR every year to European countries. Positive economic impacts from wolf presence, such as those related to reducing traffic accidents with wild ungulates or supporting wildlife tourism, remain under studied. Wolf recovery in Europe is supported by diverse policy and legal instruments such as LIFE programs, stakeholder platforms, as well as the EU Habitats Directive and the Bern Convention. Coexisting with newly established wolf populations in Europe entails managing impacts on human activities, including livestock depredation, competition for game, and fear of attacks on humans, amidst varying social and political views on wolf recovery. Sustainable coexistence continues to operate in evolving and complex social, economic, and political landscapes, often characterized by intense debates regarding wolf policies.
... Dies ist zuallererst eine gute Nachricht, zeigt sie doch, dass in Deutschland die naturräumlichen Gegebenheiten noch keine Begrenzung darstellen und auch der Tod im Straßenverkehr -mit 76 % die bisher häufigste Todesursache von Wölfen in Deutschland, deren Todesursache bekannt ist (DBBW Statusbericht Wolf 2021/22) -die Populationsentwicklung zumindest in den bisher von Wölfen besiedelten Gebieten wenig beeinträchtigt. Auch kann man davon ausgehen, dass die sogenannte ‚kryptische Mortalität', die meist auf illegale Tötungen zurückgeführt wird(Liberg et al. , 2020Sunde et al. 2021), in Deutschland verhältnismäßig niedrig ist. Die offizielle Statistik illegaler Tötungen wird mit ca. 10 % angegeben (DBBW Statusbericht Wolf 2021/22). ...
... Die offizielle Statistik illegaler Tötungen wird mit ca. 10 % angegeben (DBBW Statusbericht Wolf 2021/22). In Dänemark hingegen wurden jährliche Überlebenswerte für die Individuen zwischen 0,48 -0,54 errechnet(Sunde et al. 2021); diese Werte sind so gering, dass die dänische Wolfspopulation lediglich vorhanden ist, weil sie durch zuwandernde Tiere aus der deutschen Wolfspopulation gespeist wird. Im Vergleich dazu liegt die mittlere Überlebenswahrscheinlichkeit der deutschen Population des Wolfsbestandes in dieser Studie bei 0,81. ...
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The aim of the present study is to conduct a population viability assessment (PVA) for the wolf in Germany. This represents the first step in deriving the size of the favourable reference pop-ulation for the conservation status assessment according to article 17 Habitats Directive and simulates the development of the wolf population into the future, taking demographic sce-narios into account. Since the derivation of the reference population must necessarily take into account the connectivity to other wolf populations in neighbouring countries, a spatially-explicit, individual-based model was designed to reconstruct the expansion of the population over the last 15 years and to use it as a spatial forecasting tool for predicting population trends. The demographic data fed into the PVA come from the analysis of the nationwide wolf moni-toring data. Survival probabilities of wolves in the age classes juvenile, subadult and adult were calculated using the Cox proportional hazards regression model to simultaneously ac-count for the effects of underlying habitat quality, sex and season. Annual adult survival prob-abilities are 0.87, subadult survival probabilities are 0.75 and juvenile survival probabilities are 0.75. The annual reproductive probability of a territorial pair is 0.88, and a female has an av-erage of 4 ± 2 (SD) young per litter. Since the wolf population in Germany is expanding, the survival probabilities are in the upper range compared to other populations worldwide. The scenarios for future population development were selected in such a way that they rep-resent potential changes in natural conditions as well as natural disasters within a realistic framework. The results of the scenarios clearly show that the probability of survival had the greatest impact on the population. With a high probability of survival, the theoretical maxi-mum number of territories in Germany could be reached after only a few years; the maximum number results from the threshold of habitat suitability for establishing territories. The threshold for a stable population is above an annual mortality of approx. 40 % juveniles and subadults or approx. 30 % adults. At high mortality rates in conjunction with catastrophic events, population extinction can occur rapidly. These values for the tipping point are in line with the results of international studies. An important finding from all simulation runs, in which the population also died out with a high probability, is that the population has a 'demographic buffer' of several years due to the high survival probabilities of the previous 15 years; i.e. the population seems to continue to increase despite high mortality rates before a population collapse occurs. Conversely, this means for monitoring that long-term, closely timed monitoring is needed to detect trends in the population development in time. Although some scenarios predict a stable population development with a high probability of survival, not all of them guarantee the connectivity of the German wolf population within Ger-many and with those of neighbouring countries. Thus, connectivity requires not only stable population development, but also a core population that is vital enough to function as a con-stant source of individuals.
... Nonetheless, the observed spatial patterns of these "single" wolves are congruous with previous studies documenting non-resident behavior (Rio-Maior et al. 2019;Benson et al. 2024), supporting our assumption, within a margin of error, that they were not part of packs. Regardless of the underlying cause of single wolf activity in high-risk areas, and even after correcting for an outlier 'sink' driven by an unusual concentration of recent heavy culling, our findings align with recent studies that show human-induced mortality creates sink zones that attract dispersers from neighboring areas (Nakamura et al. 2021;Sunde et al. 2021). ...
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As wolves recolonize human-modified landscapes across the Old World, management programs aiming to mitigate livestock depredation while preserving wolf populations are falling short. The combination of human activity, habitat fragmentation, and mixed land use creates complex challenges for conservation management. Recolonized by wolves in the 1970s, the Golan Heights in northern Israel poses a dense mosaic landscape of risk, comprising grazing pastures, military zones, nature reserves, agriculture, and minefields. Today it contains one of the highest densities of wolves worldwide. While wolves are protected by law, the government maintains an active lethal management program by which about 25% of the population is culled annually. To evaluate this program’s effectiveness, we used 60 motion-triggered camera traps over 5,997 nights to monitor wolf activity across the Golan Heights. Using long-term culling and landscape data, we assessed the spatiotemporal responses of single wolves and wolf packs to culling pressure, land use and human activity. We found a positive relationship between culling pressure and single wolf activity, while pack responses to culling varied over a gradient of land uses. Single wolves utilized high-risk areas near cattle despite intense culling, while packs dominated protected, no-culling zones. Overall, culling did not deter wolves, singles or packs, from conflict zones; all zones were occupied by wolves. However, wolves shifted temporally to avoid daytime human activity and were predominantly nocturnal in high-culling areas. Understanding wolves’ responses to lethal management across diverse anthropogenic pressures offers lessons for other areas, particularly in Europe, currently undergoing wolf recolonization in similar landscapes.
... While it may not threaten the conservation of the species, poaching or illegal shooting remains a problem. The increasing number of wolves and the human pressure on the environment force them to migrate, leading to increasingly frequent traffic accidents (63). Post-mortem examinations of wolf carcasses reveal lesions indicative of multiple injuries: not only the fatal ones, but others associated with hunting large animals, i.e. red deer (Cervus elaphus), which is the main species wolf packs prey in Poland (36), or European bison (Bison bonasus) which are occasional wolf prey in the BF (35). ...
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Introduction In winter 2021/2022, a wolf population in the primeval Białowieża Forest in Poland was struck by an outbreak of severe mange caused by mixed infestations of Sarcoptes and Demodex mites. We present an epidemiological analysis of this mange which caused significant morbidity and mortality. Material and Methods Ten sites known for wolf activity were monitored by camera trapping. A diagnostic necropsy and testing of a young wolf was performed to determine the causes of death. Results Five young wolves with severe alopecia of the entire body and some other individuals with minor to medium mange lesions were identified by the camera surveillance. The necropsy of the carcass revealed emaciation, dehydration and anaemia with starvation as the cause of death, likely attributable to severe infestation with Sarcoptes scabiei and Demodex sp. mites. Rabies and infections with Borreliella sp., Anaplasma sp., Ehrlichia sp., Francisella tularensis, Babesia sp. and tick-borne encephalitis virus were excluded by specific tests. Conclusions The described analysis is the first documented co-infestation of this kind in wolves. The outbreak coincided with very mild winter conditions with a high average minimum temperature, which may have favoured mite survival outside the host, and light snowfall, which may have influenced the wolves’ ability to hunt. Other potential drivers of the outbreak could be the large proportion of wetland terrain, increasing number of wolves in the area and anthropogenic pressure on their habitats including the migration crisis at the Polish–Belarusian border and the increased presence of military and border forces, even despite the relief from the anthropogenic pressure from tourism due to the COVID-19 lockdown.
... Presently (2023), Denmark has an increasing population of c. 30 mature and 13-20 young animals (Sunde et al. 2023a, b). The re-establishment of the wolf mainly in the more desolate parts of western Jutland has sparked off an intense debate, and so far, about a third of the 54 known wolves may have been illegally shot (Sunde et al. 2021;Olsen et al. 2023). ...
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Hunting occupies a strong position in Denmark, and Danish hunters have delivered high quality data on their individual tally of bagged birds and mammals ever since it became mandatory to do so in 1941. The annual data on hunting yields of most species for more than 80 years serves to qualify the advice given by Danish wildlife biologists on hunting and wildlife management to the responsible authorities and other stakeholders. Due to overharvest or persecution many wildlife populations were heavily reduced or even driven to extinction during the last part of the nineteenth century and the first half of the twentieth century. Since then, improved legislation and management have resulted in many populations becoming re-established or increasing, and the total take by hunters increased to culminate in almost 4 million bagged mammals and birds per year around 1970. After 1970, the most distinctive pattern has been that total numbers of bagged animals has decreased, while yield in weight of the take has almost doubled over the 80-year span of data. This is because the take of smaller game has decreased due to protective measures, reduced farmland wildlife populations, and declining interest among hunters, while the take of larger species such as deer and geese has increased considerably following increasing populations resulting from improved management of hunting together with green fields in winter. The question remains as to what extent hunting and its associated disturbances and heightened shyness of wildlife keep quarry populations below the carrying capacity of the environment. This issue is particularly problematic in relation to the entire West Palearctic flyway populations of waterbirds, where lack of reliable annual bag statistics from most of the countries along the flyway prevents effective management. This challenge is further discussed in relation to societal changes in attitudes towards hunting and the future of such changes.
... As a result, wolves became strictly protected in Poland in 1998, six years before this country joined the European Union and implemented the EU Habitats Directive (Mysłajek and Nowak 2015). It stimulated the increase of the wolf population and their recovery first in western Poland , then in Germany (Jarausch et al. 2021) and the neighboring countries of northwestern Europe (Lelieveld et al. 2016, Sunde et al. 2021. ...
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We assessed the diet composition of wolves inhabiting Notecka Forest (ca 1400 km²) in western Poland based on the analysis of scats (n = 261) collected in 2008–2021. The study revealed that wolves in this large forest tract, consisting mainly of pine monocultures, consumed primarily wild ungulates (95.2% of consumed biomass). The roe deer was the essential food item (47.8%), followed by the red deer Cervus elaphus (25.1%) and the wild boar Sus scrofa) (18.4%). Wolves supplemented their diet with medium‐sized wild mammals, mainly the European hare Lepus europaeus (2.8%) and the Eurasian beaver Castor fiber (1.9%). The food niche was narrow (B = 1.1), and there was no difference in food composition between the spring–summer and autumn–winter seasons. We emphasize the significance of the smallest European wild ruminant, roe deer, in the diet of wolves inhabiting Central European Plains.
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Human‐caused mortality can be pervasive and even highly selective for individuals in groups of cooperative breeders. Many studies of cooperative breeders, however, do not address human‐caused mortality. Similarly, studies focused on the effects of human‐caused mortality on wildlife populations often do not consider the ecology of cooperative breeders. We searched the literature and identified 58 studies where human‐caused mortality affected a group characteristic, vital rate, or population state of a cooperative breeder. Of studies reporting population growth or decline, 80% reported a link between human‐caused mortality and population declines in cooperative breeders. Such studies often did not identify the mechanism behind population declines, but 28% identified concurrent declines in adult survival and another 21% reported concurrent declines in recruitment or reproduction. There was little overlap between the cooperative breeding and human‐caused mortality literatures, limiting our ability to accrue knowledge. Future work would be beneficial if it ( i ) identified the vital rate(s) causing population declines, ( ii ) leveraged management actions such as lethal removal to ask questions about the ecology of group‐living in cooperative breeders, and ( iii ) used insights from cooperative breeding theory to inform management actions and conservation of group‐living species.
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Wolves (Canis lupus) are currently showing a remarkable comeback in the highly fragmented cultural landscapes of Germany. We here show that wolf numbers increased exponentially between 2000 and 2015 with an annual increase of about 36%. We demonstrate that the first territories in each newly colonized region were established over long distances from the nearest known reproducing pack on active military training areas (MTAs). We show that MTAs, rather than protected areas, served as stepping‐stones for the recolonization of Germany facilitating subsequent spreading of wolf territories in the surrounding landscape. We did not find any significant difference between MTAs and protected areas with regard to habitat. One possible reason for the importance of MTAs may be their lower anthropogenic mortality rates compared to protected and other areas. To our knowledge, this is the first documented case where MTAs facilitate the recolonization of an endangered species across large areas.
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Despite severe population declines and an overall range contraction, some populations of large carnivores have managed to survive in human‐modified landscapes. From a conservation perspective, it is important to identify the factors allowing for this coexistence, including the relevant habitat characteristics associated with the presence of large carnivores. We evaluated the role of several environmental factors describing habitat quality for wolves Canis lupus in the humanised Iberian Peninsula, which currently holds an important wolf population at European level. We used maximum entropy and generalized linear model approaches in a nested‐scale design to identify the environmental factors that are related to wolf presence at three spatial scales and resolutions: (1) distribution range: wolf presence on a 10 × 10 km grid resolution, (2) wolf habitat use: wolf occurrence on a 2 × 2 km grid and (3) dens/rendezvous sites: breeding locations on a 1 × 1 km grid. Refuge availability, as defined by topography, seemed to be the key factor determining wolf presence at the multiple scales analysed. As a result, wolf populations may coexist with humans in modified landscapes when the topography is complex. We found that a significant amount of favourable habitat is not currently occupied, suggesting that the availability of suitable habitat is not the limiting factor for wolves in the Iberian Peninsula. Habitat suitability outside the current range indicates that other factors, such as direct persecution and other sources of anthropogenic mortality, may be hampering its expansion. We suggest that priorities for conservation should follow two general lines: (1) protect good quality habitat within the current range; and (2) allow dispersal to unoccupied areas of good quality habitat by reducing human‐induced mortality rates. Finally, we still need to improve our understanding of how wolves coexist with humans in modified landscapes at fine spatiotemporal scales, including its relationship with infrastructures, land uses and direct human presence.
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Human-driven wildlife mortality is caused by both indirect causes and direct persecution due to conflicts ofinterests. The wolf, a predator frequently at risk from human-wildlife conflict, is returning to areas where it washistorically extirpated in Scandinavia (Sweden and Norway). The wolf is expanding via a management strategythat allows wolves to reproduce exclusively in a wolf breeding range (WBR) in the south-central region. Wemodelled wolf territory occurrence in the WBR and all of Scandinavia, accounting for biotic and anthropogenicvariables, and we also modelled the occurrence of human-driven mortality (traffic collisions, culling and illegalkilling). We integrated territory distribution and mortality models in a two-dimensional model estimating ha-bitat suitability and mortality risk for wolves. Forest was the main variable driving territory occurrence, andmortality was a consequence of variables associated with traffic infrastructure, human population, prey den-sities, and wolf management levels. Only < 0.1% of the WBR was not characterized by these risks. Our resultsconfirm that human-related conflicts resulting in wolf mortality occur wherever the species is present, whichleads to actions to control the population expansion. Considering the adaptability of wolves and the presence ofpotential suitable habitat in Scandinavia, their survival and expansion will be dependent on changes in publicattitudes about illegal killing, and a review of policies and management actions. Our framework can be used toassist management of human-wildlife conflicts of recolonizing wolves elsewhere, or of other species at high riskfrom human-induced mortality.
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The first rule to poaching is that you do not talk about poaching. If you do, you do so behind a veil of anonymity, using hypotheticals or indirect reported speech that protect you from moral, cultural or legal self-incrimination. In this study of Swedish hunters talking about a phenomenon of illegal killing of protected wolves, we situate such talk in the debate between crime talk as reflecting resistance, reality or everyday venting. We identify four discourses: the discourse of silence; the complicit discourse of protecting poachers; the ‘proxy’ discourse of talking about peers; and the ‘empty’ discourse of exaggerating wolf kills as means of political resistance. Our hunters materialize these discourses both by sharing stories that we sort into respective discourses and by providing their meta-level perceptions on what they mean. Specifically we examine whether Swedish hunters’ discourses on illegal killing are (1) a means of letting off steam; (2) a reflection of reality; (3) part of a political counter-narrative against wolf conservation; or (4) a way of radicalizing peers exposed to the discourse. We conclude that illegal killing discourses simultaneously reflect reality and constitute it and that hunters’ meta-talk reveals most endorse a path-goal folk model of talk and action.
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Poaching is an important limiting factor for many large carnivore populations worldwide and the effect that legal culling has on poaching rate on wolf (Canis lupus) is debated. We used data linked to population monitoring and research to analyze rate and risk of disappearance without known cause for territorial pair-living wolves (n = 444) in Sweden 2000/01–2016/17. Known mortalities included legal kills (n = 103), natural causes (n = 23), traffic (n = 8) and verified poaching (n = 20) but most (n = 189) wolves disappeared without known cause. Careful evaluation of alternative causes supported the assumption that poaching was the most likely reason for the majority of these disappearances. Disappearance rate was0.14 for the entire study period, and increased from 0.09 in 2000/01–2009/10 to 0.21 in 2010/11–2016/17, while a Kaplan-Meier analysis on a sub-sample of radio collared wolves (n = 77) gave an average annual poaching rate of 0.12 for the entire study period and 0.10 and 0.18 for the corresponding two sub-periods. Factors affecting disappearance rate were modeled using logistic regression and Cox proportional hazards regression. Population size had a strong positive effect on disappearance rate in both models, whereas legal culling rate had a negative effect, significant only in the Cox model. The combined effect of legal culling rate and disappearance rate during the latter part of our study period has halted population growth. Our results contribute to an increased understanding of two vital drivers predicted to affect poaching rate: population size and legal culling.
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Illegal wolf kills happens around in Europe despite the European wolf is protected under the EU Habitats Directive. The reason for this is conflicts with farmers and local hunters and in some instances also direct fear. In April 2018, a wolf was killed in Denmark after 1st recolonization since the 18th century. This caused a heated debate and calls for better communication and management of the Danish and entire European wolf population. Here we discuss the challenges of illegal wolf kills and call for European governments to take action. We specifically encourage European governments to create facilitated spaces for public deliberation on wildlife management by integrating facts and values, not separating them.
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Poaching is a major threat to large predator populations, but the predictors of poaching are poorly mapped in developed countries where illegal killing is motivated by social reasons. Poaching can be common although the species is legally hunted, such as in the case of the wolf (Canis lupus). Our goal was to identify crucial motives of poaching to find possible solutions to the ongoing wolf conflict. We studied predictors of poaching on two spatial scales - countrywide (76 wolves) and territory [30 Global Positioning System (GPS)-wolves] - during 2001-2016 in Finland. The countrywide factors predicting illegal kill were as follows: (1) lifestage, with adult wolves showing a remarkably high probability of being illegally killed in comparison with juveniles; (2) the number of wolves killed legally in the local scale, that is, licensed wolf hunting at the local scale decreased the likelihood of illegal killing, as did the total number of legally hunted wolves; (3) total legal bag in the whole country; and (4) density of the local human population, that is, low human density increased the probability of illegal kill. For breeding adult GPS-collared wolves at the territory level, there was a positive relationship between the tendency to cross roads and likelihood of being illegally killed. Our results provided evidence that poaching is a matter of local intolerance toward wolves and that the problem is mainly related to wolf hunting. Legal hunting might decrease poaching, but seems inefficient as a long-term solution. To maintain a viable wolf population, the poaching risk of breeding adults should be decreased. Predicted poaching probabilities could be used to tackle poaching in a preventive manner by involving both decision makers and local residents in anti-poaching actions.
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Poaching may threaten population viability and can occur in both non-harvested and legally harvested populations. Telemetry facilitates the determination of the fates of individual animals, and the resultant mortality scenarios can be used to evaluate the role of poaching in population changes. Finland's legally hunted wolf (Canis lupus) population fluctuated between 100 and 300 animals during 1998–2016, and this cannot be explained by the rates of legal hunting and other known mortalities alone. We examined the role of poaching in wolf population changes. We created different scenarios based on multi-source information on poaching among 130 collared wolves. Poaching has been the primary cause of death followed by legal hunting. We calculated the survival rate and cause-specific mortality risk; wolves whose fates were unknown were censored. As one of the event alternatives (unknown fate or known mortality cause), censoring was related to social status; breeding adults were more often poached, whereas dispersers were censored. We created two sets of scenarios based on the censoring procedure (random and non-random), and for both sets, we created 4 scenarios ranging from high to no poaching based on decreasing confidence in the data. Annual survival ranged from 0.11–0.24 (high poaching scenario) to 0.43–0.60 (no poaching); survival dropped in mid-winter. The poaching rate varied between years from less than 0.09–0.13 up to 0.31–0.43. We consider poaching to be a regulatory factor; it focused on breeding adults and seemed to escalate as a response to increased population size. We conclude that tolerance for carnivores cannot be promoted by legal hunting alone, so more comprehensive conservation efforts are needed.