ArticlePDF Available

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

  • Senckenberg Research Institute, Gelnhausen
  • Senckenberg Research Institute and Natural History Museum Frankfurt

Abstract and Figures

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.
This content is subject to copyright. Terms and conditions apply.
Received: July  Revised:  January  Accepted:  April 
DOI: ./conl.
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
Peter Sunde, Department of Bioscience,
Aarhus University,Grenåvej , 
Rønde, Denmark.
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. 1of10./conl.
2of10 SUNDE  .
Canis lupus, Denmark, genetic wildlife monitoring, Germany, human–wildlife conflict, illegal
killings, large carnivores, poaching, recolonization, roadkills, source–sink
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.
2.1 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
2.2 Wolf monitoring in Germany and
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 (,
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
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
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 +
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  .
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 ).
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
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
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, ).
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.
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
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  ).
The data that support the findings of this study are openly
available at./RG....
The authors declare no conflicts of interest
Peter Sunde---X
Adams, L. G., Stephenson, R. O., Dale, B. W., Ahgook, R. T., &
Demma, D. J. (). Population dynamics and harvest charac-
teristics of wolves in the Central Brooks Range, Alaska. Wildlife
Andersen, L. W., Harms, V., Caniglia, R., Czarnomska, S. D., Fab-
bri, E., Jedrzejewska, B., Kluth, G., Madsen, A. B., Nowak, C.,
Pertoldi, C., Randi, E., Reinhard, I., & Stronen, A. V. ().
Long-distance dispersal of a wolf, Canis lupus, in northwest-
ern Europe. Mammal Research,60(), –..
Chapron, G., Kaczensky, P., Linnell, J. D. C., von Arx, M., Huber, D.,
Andren, H., López-Bao, J. V., Adamec, M., Álvares, F., Anders, O.,
Balčiauskas, L., Balys, V., Bedő, P., Bego, F., Blanco, J. C., Breit-
enmoser, U., Brøseth, H., Bufka, L., Bunikyte, R., ... Boitani, L.
(). Recovery of large carnivores in Europe’s modern human-
dominated landscapes. Science,346(), –. https://doi.
Chapron, G., & Treves, A. (). Blood does not buy goodwill: allow-
ing culling increases poaching of a large carnivore. Proceedings
of the Royal Society B-Biological Sciences,283(), . https://doi.
Fahrig, L., & Rytwinski, T. (). Effects of roads on animal abun-
dance: An empirical review and synthesis. Ecology and Soci-
ety,14(), . URL:/iss/
Fuller, T. K., Mech, L. D., & Cochrane, J. F. (). Wolf population
dynamics. In L. D. Mech & L. Boitani (Eds.), Wolves: Behavior,
ecology, and conservation (pp. –). Chicago, IL: University of
Chicago Press.
Grilo, C., Lucas, P. M., Fernández-Gil, A., Seara, M., Costa, G., Roque,
S., Rio-Maior, H., Nakamura, M., Álvares, F., Petrucci-Fonseca, F.,
& Revilla, E. (). Refuge as major habitat driver for wolf pres-
ence in human-modified landscapes. Animal Conservation,22(),
Heurich, M., Schultze-Naumburg, J., Piacenza, N., Magg, N., Cer-
veny, J., Engleder, T., Herdtfelder, M., Sladova, M., & Kramer-
Schadt, S. (). Illegal hunting as a major driver of the source-
sink dynamics of a reintroduced lynx population in Central
Europe. Biological Conservation,224,..
Højberg, P. L., Nielsen, M. R., & Jacobsen, J. B. (). Fear, eco-
nomic consequences, hunting competition, and distrust of author-
ities determine preferences for illegal lethal actions against gray
wolves (Canis lupus): a choice experiment among landowners in
Jutland, Denmark. Crime Law and Social Change,67(), –../s---
Liberg, O., Suutarinen, J., Åkesson, M., Andrén, H., Wabakken, P.,
Wikenros, C., & Sand, H. (). Poaching-related disappearance
rate of wolves in Sweden was positively related to population
size and negatively to legal culling. Biological Conservation,243,
Mech, L. D. (). Where can wolves live and how can we live
with them? Biological Conservation,210,.
Pohja-Mykra, M., & Kurki, S. (). Strong community support
for illegal killing challenges wolf management. European Jour-
nal of Wildlife Research,60(), –../
Pohja-Mykrä, M. (). Community power over conservation
regimes: techniques for neutralizing the illegal killing of large car-
nivores in Finland. Crime, Law and Social Change,67(), –../s---y
Primdahl, J., Bojesen, M., Vesterager, J. P., & Kristensen, L. S. ().
Hunting and landscape in Denmark: Farmers’ management of
hunting rights and landscape changes. Landscape Research,37(),
Recio, M. R., Zimmermann, B., Wikenros, C., Zetterberg, A.,
Wabakken, P., & Sand, H. (). Integrated spatially-explicit mod-
els predict pervasive risks to recolonizing wolves in Scandinavia
from human-driven mortality. Biological Conservation,226, –
Reinhardt, I., Kluth, G., Nowak, C., Szentiks, C. A., Krone, O.,
Ansorge, H., & Mueller, T. (). Military training areas facili-
tate the recolonization of wolves in Germany. Conservation Letters,
12(), e../conl.
Sonne, C., Hansen, H. P., Alstrup, A. K. O., Olsen, K., Jensen, T. H.,
Haugaard, L., & Sunde, P. (). Discussion: Illegal kills of pro-
tected wolves call for public reasoning. Science of the Total Envi-
Sunde, P., & Olsen, K. (). Ulve (Canis lupus) i Danmark
2012–2017: Oversigt og analyse af tilgængelig bestandsinformation.
Aarhus University, DCE Nationalt Center for Miljø og Energi,
report  ( pp.) URL:. http://dce.pdf
Suutarinen, J., & Kojola, I. (). Poaching regulates the legally
hunted wolf population in Finland. Biological Conservation,215,
Suutarinen, J., & Kojola, I. (). One way or another: predic-
tors of wolf poaching in a legally harvested wolf population.
Animal Conservation,21(), –../acv.
10 of 10 SUNDE  .
Treves, A., & Bruskotter, J. (). Tolerance for predatory wildlife.
Science,344(), –../science.
Treves, A., Langenberg, J. A., Lopez-Bao, J. V., & Rabenhorst, M.
F. (). Gray wolf mortality patterns in Wisconsin from  to
. Journal of Mammalogy,98(), –../
von Essen, E., Hansen, H. P., Kallstrom, H. N., Peterson, M. N., &
Peterson, T. R. (). The radicalisation of rural resistance: How
hunting counterpublics in the Nordic countries contribute to ille-
gal hunting. Journal of Rural Studies,39, –.
von Essen, E., Hansen, H. P., Peterson, M. N., & Peterson, T. R. ().
Discourses on illegal hunting in Sweden: the meaning of silence
and resistance. Environmental Sociology,4(), –. https://./..
Additional supporting information may be found online
in the Supporting Information section at the end of the
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../conl.
... European studies have documented the extent of human-caused mortality in different large carnivore species, with poaching and vehicular collisions accounting for up to 46% of the total mortality (Andrén et al., 2006;Heurich et al., 2018;Liberg et al., 2012;Sunde et al., 2021). In Yellowstone National Park (USA), however, ...
Full-text available
Terrestrial ecosystems are shaped by interacting top‐down and bottom‐up processes, with the magnitude of top‐down control by large carnivores largely depending on environmental productivity. While carnivore‐induced numerical effects on ungulate prey populations have been demonstrated in large, relatively undisturbed ecosystems, whether large carnivores can play a similar role in more human‐dominated systems is a clear knowledge gap. As humans influence both predator and prey in a variety of ways, the ecological impacts of large carnivores can be largely modified. We quantified the interactive effects of human activities and large carnivore presence on red deer ( Cervus elaphus ) population density and how their impacts interacted and varied with environmental productivity. Data on red deer density were collected based on a literature survey encompassing 492 study sites across 28 European countries. Variation in density across study sites was analysed using a generalized additive model in which productivity, carnivore presence (grey wolf, European lynx, Brown bear), human activities (hunting, intensity of human land‐use activity), site protection status and climatic variables served as predictors. The results showed that a reduction in deer density only occurred when wolf, lynx and bear co‐occurred within the same site. In the absence of large carnivores, red deer density varied along a productivity gradient without a clear pattern. Although a linear relationship with productivity in the presence of all three large carnivore species was found, this was not statistically significant. Moreover, hunting by humans had a stronger effect than the presence of all large carnivores in reducing red deer density and red deer density increased with increasing intensity of human land use, with stronger large carnivore effects (all three carnivore species present) at sites with low human land‐use activities. Synthesis and applications . This study provides evidence for the dominant role played by humans (i.e. hunting, land‐use activities) relative to large carnivores in reducing red deer density across European human‐dominated landscapes. These findings suggest that when we would like large carnivores to exert numeric effects, we should focus on minimizing human impacts to allow the ecological impacts of large carnivores on ecosystem functioning.
... These positive and negative aspects of returning wolves typically result in a highly polarized public attitude towards this iconic species (Arbieu et al., 2019;Treves et al., 2004). Although wolves are protected in most European countries including Germany (Chapron et al., 2014), illegal killing as retaliation for livestock depredation, in fear of competition for game and fear of wolves became a major source of wolf mortality (Ansorge et al., 2006;Bautista et al., 2019;Linnell & Alleau, 2016;Nowak et al., 2021;Sunde et al., 2021;Suutarinen & Kojola, 2017). Understanding where wolves are likely to expand is therefore urgently needed to proactively manage potential conflicts and to foster co-existence. ...
Full-text available
Aim The non‐stationarity in habitat selection of expanding populations poses a significant challenge for spatial forecasting. Focusing on the grey wolf (Canis lupus) natural recolonization of Germany, we compared the performance of different distribution modelling approaches for predicting habitat suitability in unoccupied areas. Furthermore, we analysed whether grey wolf showed non‐stationarity in habitat selection in newly colonized areas, which will impact the predictions for potential habitat. Location Germany. Methods Using telemetry data as presence points, we compared the predictive performance of five modelling approaches based on combinations of distribution modelling algorithms—GLMM, MaxEnt and ensemble modelling—and two background point selection strategies. We used a homogeneous Poisson point process to draw background points from either the minimum convex polygons derived from telemetry or the whole area known to be occupied by wolves. Models were fit to the data of the first years and validated against independent data representing the expansion of the species. The best‐performing approach was then used to further investigate non‐stationarity in the species' response in spatiotemporal restricted datasets that represented different colonization steps. Results While all approaches performed similarly when evaluated against a subset of the data used to fit the models, the ensemble model based on integrated data performed best when predicting range expansion. Models for subsequent colonization steps differed substantially from the global model, highlighting the non‐stationarity of wolf habitat selection towards human disturbance during the colonization process. Main Conclusions While telemetry‐only data overfitted the models, using all available datasets increased the reliability of the range expansion forecasts. The non‐stationarity in habitat selection pointed to wolves settling in the best areas first, and filling in nearby lower‐quality habitat as the population increases. Our results caution against spatial extrapolation and space‐for‐time substitutions in habitat models, at least with expanding species.
... However, considerable wolf mortality is human-caused (Hill et al., 2022), so wolf persistence depends on sustainable coexistence with humans, particularly in areas of lower suitability, which may have greater human disturbance, lower prey abundance, and higher livestock densities (Gompper et al., 2015;Treves & Karanth, 2003). Areas where human-wolf coexistence is not attainable could act as population sinks (Lamb et al., 2020;Sunde et al., 2021). ...
Full-text available
Land use and climate change alter species distributions worldwide, and detecting and understanding how species ranges shift can facilitate conservation planning and action. Following extirpation from most of the contiguous United States, gray wolves ( Canis lupus ) have partially recolonized former range in the western Great Lakes region, but it is unknown how land use and climate change may alter amounts of wolf habitat. Using wolf observation data collected during winters 2017–2020 in Minnesota, Wisconsin, and Michigan, we created ensemble models to predict how land use and climate change may affect the amount of wolf habitat within these states. A projection model for the western Great Lakes region suggested three of four scenarios of land use and climate change will lead to 9%–35% increases in wolf habitat, while a solely climate‐based projection model supported our expectation that changes in climate, in isolation, will have limited effect on current wolf range. Our results support stable or increasing amounts of wolf habitat in the western Great Lakes region during the 21st century, suggesting limited or no adverse effects on the current distribution or further recolonization of wolves. Our findings can inform policy development regarding wolf conservation and identify areas where recolonization is plausible, thus where promoting human–wolf coexistence is most pertinent.
... Recent studies have documented human attitudes becoming more negative toward wolves after their killing was legalized for a period of time [23][24][25][26] . Remarkably, Fuller 27 reported similarly high levels of wolf mortality in a 1980-1985 radio-tracking study of 81 wolves, with even higher human-caused mortality than that observed following the 2012-2014 hunting and trapping seasons-even though the wolf population was smaller in the 1980s. ...
Full-text available
By the mid-twentieth century, wolves were nearly extinct in the lower 48 states, with a small number surviving in northern Minnesota. After wolves were placed on the endangered species list in 1973, the northern Minnesota wolf population increased and stabilized by the early 2000s. A wolf trophy hunt was introduced in 2012–2014 and then halted by a court order in December 2014. The Minnesota Department of Natural Resources collected wolf radiotelemetry data for the years 2004–2019. Statistical analysis showed that wolf mortality remained close to constant from 2004 until the initiation of the hunt, and that mortality doubled with the initiation of the first hunting and trapping season in 2012, remaining at a nearly constant elevated level through 2019. Notably, average annual wolf mortality increased from 21.7% before wolf hunting seasons (10.0% by human causes and 11.7% natural causes) to 43.4% (35.8% by human causes and 7.6% natural causes). The fine-grained statistical trend implies that human-caused mortality increased sharply during the hunting seasons, while natural mortality initially dropped. After the hunt’s discontinuation, human-caused mortality remained higher than prior to the hunting seasons throughout the five years of the available after-hunt radiotelemetry data.
... Provided that this heterogeneity in long-term selective pressures might have turned into a different capacity of exploiting human-dominated landscapes, the situation between Italy and other countries from Southern, Central and Eastern Europe, some of whom have indeed been colonized by individuals from the Italian peninsula (e.g., France) [27], seems to be temporally lagged, but following a rather similar trajectory. Wolves are progressively colonizing humandominated landscapes, initially with single dispersing individuals or couples [33][34][35], and then either with source-sink dynamics [36,37] and or with well-established packs [38,39] a process that in Italy has been observed 20-15 years ago. Therefore, understanding the suitability of anthropized areas for wolves in Italy, a country where wolf colonization is at a more advanced stage, could be pivotal to evaluate the extent to which the species could re-occupy its historical range in Europe and to forecast the spatial scale of future mitigation measures or zonation policies [40]. ...
Full-text available
The gray wolf (Canis lupus) expanded its distribution in Europe over the last few decades. To better understand the extent to which wolves could re-occupy their historical range, it is important to test if anthropization can affect their fitness-related traits. After having accounted for ecologically relevant confounders, we assessed how anthropization influenced i) the growth of wolves during their first year of age (n = 53), ii) sexual dimorphism between male and female adult wolves (n = 121), in a sample of individuals that had been found dead in Italy between 1999 and 2021. Wolves in anthropized areas have a smaller overall variation in their body mass, during their first year of age. Because they already have slightly higher body weight at 3-5 months, possibly due to the availability of human-derived food sources. The difference in the body weight of adult females and males slightly increases with anthropization. However, this happens because of an increase in the body mass of males only, possibly due to sex-specific differences in dispersal and/or to "dispersal phenotypes". Anthropization in Italy does not seem to have any clear, nor large, effect on the body mass of wolves. As body mass is in turn linked to important processes, like survival and reproduction, our findings indicates that wolves could potentially re-occupy most of their historical range in Europe, as anthropized landscapes do not seem to constrain such of an important life-history trait. Wolf management could therefore be needed across vast spatial scales and in anthropized areas prone to social conflicts.
Wolves and other wildlife species that share habitats with humans with minor options for spatial avoidance must either tolerate frequent human encounters, which may be lethal, or allocate their activity to those periods of the day when the risk of encountering humans is smallest and the consequences least severe. This may force wolves in densely human-populated and cultivated landscapes to either become highly nocturnally active or habituate to human stimuli. Based on 6,220 camera trap images of adult wolves from eight territories in Denmark, we analyzed the extent to which diel activity patterns in a wolf population in a highly cultivated landscape with fragmented forests and extensive public access could be explained from diel variation in darkness, human activity, and prey (deer) activity. We found that diel activity correlated with all three factors simultaneously with human activity (negative) having the strongest total as well as partial effect, followed by darkness (positive) and deer activity (positive). Relative to a model that smoothed activity as a function of time of the day, the three factors accounted for 94% of the explainable diel variation in wolf activity. As most of the apparent selection for darkness could be explained by temporal human avoidance, we suggest that nocturnality (proportion of observations registered at night vs. day at equinox) is a useful proxy for investment in temporal human avoidance. In this study, wolf packs were 7.0 (95% CI: 5.0-9.7) times more active at night than at daytime, which makes Danish wolves amongst the most nocturnally active wolves reported so far. This result confirms the initial prediction that wolves with few options for spatial avoidance, invest heavily in temporal human avoidance.
Wolves are one of the most studied wildlife species in the world, yet we only have an emerging picture of how humans affect wolf social dynamics. This chapter provides an overview of wolf social dynamics, including the fundamentals of how they live, breed, hunt, and survive, the advantages and disadvantages that coincide with group living, and how human pressures may affect their social behavior. Wolves are a short-lived species with a fast-paced life history who display a high degree of behavioral flexibility. Their primary social unit is a multigenerational family group, also called a “pack.” Group dynamics (e.g., number of individuals, age structure, composition, and cohesion) and foraging strategies (e.g., prey selection, hunting tactics, and scavenging behavior) vary widely and are generally context dependent. In other words, they differ between systems, seasons, prey type, size and density, the density of conspecifics and other competitors, habitat type and landscape characteristics, and levels of anthropogenic disturbance. Regardless of the system, group living provides a range of advantages to wolves, including territorial defense, breeding, hunting, and food defense. However, these must be balanced with inherent disadvantages of group living, such as intraspecific competition within the pack, e.g., competition for food. Anthropogenic disturbance can directly and indirectly alter wolf behavior. For example, wolves alter their spatial and temporal movement patterns and space use within human-modified landscapes and in response to human disturbance, which can dampen their ecological role as apex predators. Humans also directly affect pack dynamics and social behavior by killing individuals, via both legal and illegal harvest. By reviewing recent research conducted on wolf populations living under different levels of protection, we suggest that wolf pack social structure appears to be comparatively more complex (i.e., include more age classes and complex relationships) in systems where anthropogenic mortality is low. In addition, high anthropogenic mortality across all age and sex classes may alter dispersal patterns and reduce pack cohesion and functionality, which may ultimately foster pack dissolution. In turn, this may increase pack turnover rates and reduce both individual lifespan and pack longevity, with potentially relevant ecological and conservation implications. The consequences of anthropogenic disturbance on social dynamics is likely particularly important, as there are few wolf populations inhabiting landscapes free from humans and their impact. Wolves are often considered a resilient species, meaning you can hunt them and their numbers will quickly rebound. Indeed, wolves may appear numerically resilient, but their pack composition and social dynamics are likely more fragile. This is important because changes to pack size and composition can affect a pack’s ability to successfully hunt prey, rear pups, and defend their territories, as well as their overall ecology, population dynamics, and cascading effects through an ecosystem.
Full-text available
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.
Full-text available
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.
Full-text available
Starting in the 1970s, many populations of large-bodied mammalian carnivores began to recover from centuries of human-caused eradication and habitat destruction. The recovery of several such populations has since slowed or reversed due to mortality caused by humans. Illegal killing (poaching) is a primary cause of death in many carnivore populations. Law enforcement agencies face difficulties in preventing poaching and scientists face challenges in measuring it. Both challenges are exacerbated when evidence is concealed or ignored. We present data on deaths of 937 Wisconsin gray wolves (Canis lupus) from October 1979 to April 2012 during a period in which wolves were recolonizing historic range mainly under federal government protection. We found and partially remedied sampling and measurement biases in the source data by reexamining necropsy reports and reconstructing the numbers and causes of some wolf deaths that were never reported. From 431 deaths and disappearances of radiocollared wolves aged > 7.5 months, we estimated human causes accounted for two-thirds of reported and reconstructed deaths, including poaching in 39-45%, vehicle collisions in 13%, legal killing by state agents in 6%, and nonhuman causes in 36-42%. Our estimate of poaching remained an underestimate because of persistent sources of uncertainty and systematic underreporting. Unreported deaths accounted for over two-thirds of all mortality annually among wolves > 7.5 months old. One-half of all poached wolves went unreported, or > 80% of poached wolves not being monitored by radiotelemetry went unreported. The annual mortality rate averaged 18% ± 10% for monitored wolves but 47% ± 19% for unmonitored wolves. That difference appeared to be due largely to radiocollaring being concentrated in the core areas of wolf range, as well as higher rates of human-caused mortality in the periphery of wolf range. We detected an average 4% decline in wolf population growth in the last 5 years of the study. Because our estimates of poaching risk and overall mortality rate exceeded official estimates after 2012, we present all data for transparency and replication. More recent additions of public hunting quotas after 2012 appear unsustainable without effective curtailment of poaching. Effective antipoaching enforcement will require more accurate estimates of poaching rate, location, and timing than currently available. Independent scientific review of methods and data will improve antipoaching policies for large carnivore conservation, especially for controversial species facing high levels of human-induced mortality.
Full-text available
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.
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.
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.
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. Wolf populations may coexist with humans in modified landscapes when the topography is complex. A significant amount of favourable habitat is not currently occupied. 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. Photo Credit : Joaquim Pedro Ferreira
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.
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.