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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
(GWm) 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, GWm and
GWf (estimated disappeared c. January , and July , by method ) was coded as alive in the analysis. Multiple possible birth
dates of GWm 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
andborninDK(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 (GWm) 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
% year−during – (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 GWm. 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 GWm 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
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https://doi.org/./conl.
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