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Management plan for the brown bear Ursus arctos in Poland

Authors:
Nuria Selva at Polish Academy of Sciences
Nuria Selva
Tomasz Zwijacz-Kozica at Tatra National Park
Tomasz Zwijacz-Kozica
  • Tatra National Park
Agnieszka Sergiel at Institute of Nature Conservation, Polish Academy of Sciences, Krakow
Agnieszka Sergiel
  • Institute of Nature Conservation, Polish Academy of Sciences, Krakow
Agnieszka Olszanska at Polish Academy of Sciences
Agnieszka Olszanska
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MANAGEMENT'PLAN'
FOR'THE'BROWN'BEAR'IN'POLAND
DRAFT'
November'2011'
Authors:'
Nuria& Selva,& Tomasz& Zwijacz5Kozica,& Agnieszka& Sergiel,& Agnieszka&
Olszańska,&Filip&Zięba&
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!!
3
List%of%figures:%
Fig.%1.%Distribution%of%the%brown%bear%in%Poland%in%2009:2011%according%to%the%data%gathered%
and%following%the%geographical%system%of%the%Atlas%of%Polish%Mammals.%..................................%14%
Fig.%2.%Brown%bear%records%in%the%Polish%Carpathians%in%2009:2011,%including%females%with%cubs%
and%damages.%..............................................................................................................................%15%
Fig.%3.%Predicted%model%of%habitat%suitability%for%the%brown%bear%in%Poland%and%Slovakia.%.........%41%
Fig.%4.%Ecological%corridors%and%critical%points%(current%and%potential)%in%the%Polish%Carpathians.
%....................................................................................................................................................%46%
Fig.%5.%Unfragmented%areas%in%the%Polish%Carpathians,%identified%as%those%further%than%500%m%
from%the%closest%road%or%trail%......................................................................................................%48%
%
List%of%tables:%
Table%1.%Current%status%of%the%brown%bear%population%in%the%Carpathian%countries%according%to%
the%conservation%status%national%reports%....................................................................................%11
Table%2.%Preliminary%results%of%brown%bear%genetic%monitoring%conducted%in%the%main%Polish%
bear%refuges%during%2010.%...........................................................................................................%12
Table%3.%Summary%of%the%different%stages,%tasks%and%timeframe%for%the%different%branches%of%
the%brown%bear%monitoring%program%in%Poland%..........................................................................%34
Table%4.%Estimated%costs%for%each%part%of%the%monitoring%program.%...........................................%38
Table%5.%Schedule%of%the%monitoring%program%in%Poland%for%the%period%2012:2025.%..................%38
Table%6.%Compensation%costs%(PLN)%paid%annually%for%damages%caused%by%brown%bears%in%the%
areas%of%brown%bear%occurrence%in%the%period%2003%:%2010%%......................................................%54
Table%7.%The%classification%of%risk%assessments%based%on%bear%behavior%and%recommended%
actions.%In%brackets,%actions%that%may%be%also%recommended%depending%on%the%situation%%......%58
Table%8.%Schedule%for%the%implementation%of%the%recommended%actions.%.................................%77
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11
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12
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14
!
Fig.!2.!Brown!bear!records!in!the!Polish!Carpathians!in!2009:2011,!including!females!with!cubs!and!damages.!
15
4.#Goals#of#the#management#plan##
!"#$%&'&()$(*$+"&'$,-.)$ &'$+"#$preservation# of#a#viable# natural#brown#bear#population#
and#its# habitat#in#a#favourable#conservation#status#in#coexistence#with#humans.#!"&'$
%&'&()$ /#*-#0+'$ .)$ #0('1'+#2$ .,,/(.0"$ .)3$ 0.--'$ *(/$ ,/(2(+&)4$ +"#$ 5#./'6$ ).+7/.-$
5#".%&(/8$ ,/#'#/%&)4$ +"#&/$ ).+7/.-$ ".5&+.+8$ 2.&)+.&)&)4$ #0(-(4&0.-$ ,/(0#''#'$ .)3$
0()'&3#/&)4$5#./'$.'$.)$&2,(/+.)+$#-#2#)+$(*$*(/#'+$#0('1'+#2'9$!"#$,-.)$.-'($.&2'$.+$
,/(%&3&)4$reliable#data#and# detailed$guidelines$ +($.7+"(/&+&#'$.)3$2.).4#/'$+($ '(-%#$
#:&'+&)4$ (/$ ,(+#)+&.-$ 0()*-&0+'$ .)3$ +.;#$ 2.).4#2#)+$ 3#0&'&()'$ 5.'#3$ ()$ scientific#
evidence.$
!"#$4#)#/.-$4(.-$(*$+"#$2.).4#2#)+$,-.)$*(/$+"#$5/(<)$5#./$&)$=(-.)3$&'$to#guarantee#
the#long:term#conservation#of#the#species#and#its#habitat#by#providing#the#managers,#
authorities# and# interest# groups# with# effective# conservation# measures,# precise#
information# on# the# population# and# habitat#conservation# status# and# guidelines# to#
prevent#and/or#solve#the#conflicts#with#humans9$!"#$,-.)$<&--$'#+$+"#$*/.2#<(/;$*(/$
+"#$ 0((/3&).+&()$ (*$ +"#$ 2.).4#2#)+$ 2#.'7/#'$ .)3$ *(/$ *7+7/#$ 3#0&'&()'$ 5.'#3$ ()$
'0&#)+&*&0$ 3.+.$ .)3$ 2()&+(/&)49$ !"&'$ 4(.-$ <&--$ 5#$ .00(2,-&'"#3$ ()-1$ &*$ +"#$ *(--(<&)4$
',#0&*&0$(5>#0+&%#'$./#$.0"&#%#3?$
@AB =/#'#/%#$+"#$).+7/.-$5#./$".5&+.+$.)3$&+'$C7.-&+19$
@DB =/#%#)+8$ /#.0+$ +($ .)3$ ,/(%&3#$ '(-7+&()'$ +($ .--$ ;&)3'$ (*$ "72.)E5#./$ 0()*-&0+$
'&+7.+&()'9$
@FB G%(&3$5#./$".5&+7.+&()$.)3$*((3$0()3&+&()&)49$
@HB I&)&2&J#$5#./$3.2.4#'8$#',#0&.--1$+($5##"&%#'9$
@KB =/#'#/%#$ .)3$ &2,/(%#$ +"#$ 0())#0+&%&+1$ 5#+<##)$ +"#$ /#,/(370+&%#$ )70-#&$ &)$ +"#$
<#'+#/)$.)3$#.'+#/)$=(-&'"$L./,.+"&.)'9$$
@MB I.&)+.&)$.$'+.5-#$.)3$0()+&)7(7'$5#./$,(,7-.+&()$.-()4$ +"#$)(/+"#/)$L./,.+"&.)$
/.)4#$&)$0((,#/.+&()$<&+"$N-(%.;&.$.)3$O;/.&)#9$$
16
@PB Q#0/#.'#$.)3$0()+/(-$5/(<)$5#./$2(/+.-&+1$37#$+($"72.)$*.0+(/'9$
@RB S2,-#2#)+$ .$ '(-&3$ .)3$ 0("#/#)+$ 2()&+(/&)4$ ,/(4/.2$ .)3$ 0/#.+#$ .$ /#-&.5-#$ .)3$
.%.&-.5-#$5/(<)$5#./$Q.+.$T.);9$
@UB =/(2(+#$+"#$0((/3&).+&()$(*$2.).4#2#)+$.0+&%&+&#'$.)3$&)*(/2.+&()$*-(<$.2()4$
&)%(-%#3$'#0+(/'9$
@AVB S2,/(%#$+"#$'0&#)+&*&0$.)3$,75-&0$;)(<-#34#$()$+"#$',#0&#'$&)$=(-.)39$$
@AAB W##,$+"#$,75-&0$&)*(/2#3$51$2.;&)4$.%.&-.5-#$2()&+(/&)4$3.+.$.)3$.))7.-$/#,(/+'9$
@ADB X'+.5-&'"$ .$ ,#/2.)#)+$ .)3$ 0-('#$ 0((,#/.+&()$ <&+"$ N-(%.;&.$ .)3$ O;/.&)#$ .)3$
&)0/#.'#$+"#$&)+#/).+&().-$0((,#/.+&()9$
@AFB =/(2(+#$,75-&0$.<./#)#''$.)3$,./+&0&,.+&()$&)$5/(<)$5#./$&''7#'$.)3$2()&+(/&)49$$
@AHB S2,/(%#$+"#$-&%&)4$0()3&+&()'$(*$0.,+&%#$5#./'9$
@AKB =/(2(+#$#)%&/()2#)+.-$#370.+&()$&)$.--$'(0&.-$'#0+(/'9$
@AMB Y7./.)+##$ +"#$ ,/(,#/$ &2,-#2#)+.+&()$ (*$ +"#$ #:&'+&)4$ -#4&'-.+&()$ .)3$ .$ /#.-$
,/(+#0+&()$(*$5/(<)$5#./'$.)3$+"#&/$".5&+.+9$
$
17
5.#Tools# for# the# implementation# of# the# management#
plan#
!"#$0((/3&).+&()$(*$.--$,./+&#'$&)%(-%#3$&'$+"#$*&/'+$.)3$2('+$&2,(/+.)+$'+#,8$.)3$()#$(*$
+"#$ 2.&)$ (5>#0+&%#'$ (*$ +"#$ ,/#'#)+#3$ ,-.)9$ !"#$ #'+.5-&'"2#)+$ (*$ +"#$ T#./$ Z(/;&)4$
Y/(7,8$T#./$X2#/4#)01$ !#.28$T#./$Q.+.$T.);8$ .)3$N+.)3./3$=/(+(0(-'$./#$ ,/(,('#3$
.'$ +"#$ 2('+$ #**#0+&%#$ +((-'$ *(/$ +"#$ &2,-#2#)+.+&()$ (*$ +"#$ 2.).4#2#)+$ ,-.)9$ !"#1$
/#,/#'#)+$.)$.)'<#/$+($+"#$,((/$0((/3&).+&()$&)$/#-.+&()$+($+"#$.%.&-.5&-&+1$(*$3.+.$.)3$
&)*(/2.+&()8$0()'#/%.+&()$.)3$ /#'#./0"$.0+&%&+&#'$.)3$ 0(227)&0.+&()9$!"#$7)3#/-1&)4$
&3#.'$ +".+$ *(/2$ +"#$ 5.'&'$ (*$ +"#'#$ ,/(,('.-'$ ./#$ +/.)',./#)018$ &)%(-%#2#)+$ (*$ .--$
&)+#/#'+#3$4/(7,'$&)$5#./$2.).4#2#)+8$+#.2<(/;$.)3$'+/()4$0((,#/.+&()$<&+"&)$+"#$
4/(7,8$.'$<#--$.'$.)$(,#)$.00#''$+($&)*(/2.+&()$.)3$3.+.9$Q#+.&-#3$&)*(/2.+&()$()$+"#$
+((-'$+($&2,-#2#)+$+"#$2.).4#2#)+$,-.)$&'$,/(%&3#3$&)$G))#:$A9$
$
5.1.#Bear#Working#Group#
!"#$ 0()0#,+$ (*$ +"#$ ,/(,('#3$ T#./$ Z(/;&)4$ Y/(7,$ &'$ 5.'#3$ ()$ +"#$ #:,#/&#)0#'$ (*$
<(/;&)4$4/(7,'$*/(2$(+"#/$0(7)+/&#'9$!"#'#$#:,#/&#)0#'$'"(<$+".+$+"#$0((/3&).+&()$(*$
2.).4#2#)+$.0+&()'$51$.$4/(7,$(*$#:,#/+'$&'$.$47./.)+##$*(/$.$"&4"EC7.-&+1$(7+,7+$.)3$
&)*(/2.+&()$*-(<$.)3$#:0".)4#9$!"#$T#./$Z(/;&)4$Y/(7,$&'$.$0(2,#+#)+8$+/.)',./#)+$
.)3$3#2(0/.+&0$5(31$+".+$,/(%&3#'$'75'+.)+&.-$'7,,(/+$*(/$.--$,(,7-.+&()$2.).4#2#)+$
&''7#'8$0((/3&).+#'$2#.'7/#'$.)3$.0+&%&+&#'8$.)3$'7,#/%&'#'$+"#$&2,-#2#)+.+&()$(*$+"#$
2.).4#2#)+$ ,-.)9$ !"#$ Y/(7,$ &'$ *(/2#3$ 51$ .)$ interdisciplinary# team$ (*$ '0&#)+&'+'8$
5&(-(4&'+'8$ 0()'#/%.+&()$ #:,#/+'8$ %#+#/&)./&.)'8$ [Y\'$ .)3$ .32&)&'+/.+&()$
/#,/#'#)+.+&%#'$.)3$&'$5.'#3$ ()$+"#$%(-7)+./1$&)%(-%#2#)+$(*$ &+'$2#25#/'9$!"#$T#./$
Z(/;&)4$Y/(7,$<&--$5#$*(/2.--1$#'+.5-&'"#3$51$+"#$3#0&'&()$(*$+"#$"#.3$(*$+"#$Y#)#/.-$
Q&/#0+(/.+#$*(/$X)%&/()2#)+.-$=/(+#0+&()8$ <"($ <&--$.-'($.00#,+$+"#$Y/(7,6'$ /7-#'$.)3$
51-.<'9$G--$&)*(/2.+&()$ .)3$/#,(/+'$()$+"#$.0+&%&+&#'$(*$+"#$ Y/(7,$<&--$5#$ .%.&-.5-#$+($
+"#$,75-&09$!"#$Y/(7,$ .0+'$ .'$ .)$ &)3#,#)3#)+$ .)3$ .3%&'(/1$ 5(31$ *(/$ +"#$ I&)&'+/1$ (*$
X)%&/()2#)+8$.)3$Y#)#/.-$.)3$]#4&().-$Q&/#0+(/.+#'$*(/$X)%&/()2#)+.-$=/(+#0+&()9$
18
Objective#and#structure#
!"#$ ,/&2./1$ (5>#0+&%#$ (*$ +"#$ #'+.5-&'"2#)+$ (*$ +"#$ T#./$ Z(/;&)4$ Y/(7,$ &'8$
&)$.4/##2#)+$ <&+"$ +"('#$ (*$ +"#$ 2.).4#2#)+$ ,-.)8$ an# effective# protection# and#
coordination#of#the#brown#bear#population#management#in#Poland,#guaranteeing#the#
survival# of# the# species# and# the# maintenance# of# a# viable# population# in# a# favourable#
conservation#status#in#coexistence#with#humans9$!"#$Y/(7,$<&--$,/(2(+#$.)3$'7,,(/+$
+"#$&2,-#2#)+.+&()$(*$ +"#$,-.)8$&3#)+&*1$2.).4#2#)+$ &''7#'$.)3$'#+$ 7,$,/&(/&+&#'$*(/$
0()'#/%.+&()$2#.'7/#'$.)3$,(,7-.+&()$2.).4#2#)+8$ .'$ <#--$ .'$*(/$/#'#./0"8$0.,+&%#$
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X370.+&()$.)3$L(227)&0.+&()$(*$+"#$T#./$Z(/;&)4$Y/(7,9$!"#$TX!$&'$0()+&)7(7'-1$
<(/;&)4$ +($ &2,/(%#$ +"#$ '0"#2#$ (*$ &)*(/2.+&()$ *-(<8$ <(/;&)4$ ,/(+(0(-$ .)3$
,/(0#37/#'$37/&)4$&)+#/%#)+&()'9$$
_(/$.33&+&().-$&)*(/2.+&()8$'##$G))#:$A9$
#
5.3.#Bear#Data#Bank#
The#coordination#of#monitoring#and#data#collection#is#an#integral#part#of#any#effective#
population#management9$!($4.+"#/$+"#$/#'7-+'$(*$5/(<)$5#./$,(,7-.+&() .)3$".5&+.+$
2()&+(/&)4$&)$=(-.)38$.'$<#--$.'$5/(<)$5#./$'.2,-#'8$&)*(/2.+&()$()$3#.3$&)3&%&37.-'8$
3.2.4#'$ 0.7'#3$ 51$ 5#./'8$ (/$ "72.)E5#./$ 0()*-&0+'$ &)+($ ()#$ 0(22()$ &)*(/2.+&()$
'1'+#2$&'$()#$ (*$+"#$;#1$#-#2#)+'$ *(/$.0"&#%&)4$.$4((3$ ;)(<-#34#$(*$+"#$,(,7-.+&()$
.)3$3(072#)+&)4$+/#)3'9$Y&%#)$+"#$07//#)+$.5'#)0#$(*$'70"$'1'+#28$+"#$*/.42#)+.+&()$
.)3$ )()E.%.&-.5&-&+1$ (*$ &)*(/2.+&()8$ .)3$ +"#$ -.0;$ (*$ '+.)3./3&J.+&()$ (*$ 2()&+(/&)4$
24
2#+"(3'$.)3$,/(+(0(-'8$ +"#$,/(,('#3$0/#.+&()$(*$ .$0#)+/.-$T#./$Q.+.$ T.);$&'$crucial9$
!"#$.%.&-.5&-&+1$(*$+"#$3.+.$0(--#0+#3$&)$+"#$Q.+.$T.);$<&--$,/(2(+#$/#'#./0"$'+73&#'$
.)3$ -./4#-1$ &2,/(%#$ +"#$ 07//#)+$ ;)(<-#34#$ ()$ +"#$ 5#./$ ,(,7-.+&()9$ !"#$ T#./$ Q.+.$
T.);$ .-'($ .&2'$ +($ 5#$ .$ +/.)',./#)+$ 5(318$ #'+.5-&'"$ .,,/(,/&.+#$ ,(-&0&#'$ ()$ 3.+.$
.%.&-.5&-&+1$.)3$7'#8$&2,/(%#$3.+.$0(--#0+&()$+"/(74"$'+.)3./3&J.+&()$(*$,/(+(0(-'8$.)3$
,/(2(+#$+"#$7'#$(*$#:&'+&)4$3.+.$.)3$'7,,(/+$/#'#./0"9$$
!"#$ T#./$ Q.+.$ T.);$ <&--$ 2.&)+.&)$ /#0(/3'$ (*$ +"#$ #:&'+&)4$ &)*(/2.+&()$ ()$ +"#$
,(,7-.+&()8$ ,./+&07-./-1$ +"#$ results# of# monitoring,# Standard# Protocols,# intervention#
protocols# and# the# archive# for# biological# samples9$ !"#$ Y#)#/.-$ Q&/#0+(/.+#$ *(/$
X)%&/()2#)+.-$=/(+#0+&()$<&--$.,,(&)+ +"#$ &)'+&+7+&()$/#',()'&5-#$+($./0"&%#$3.+.$ .)3$
'.2,-#'$.)3$+($2.&)+.&)$+"#$T.);9 G))7.-$/#,(/+'$ ()$ +"#$ 07//#)+$ '+.+7'$ (*$+"#$T#./$
Q.+.$T.);$.)3$+"#$(7+,7+'$*/(2$+"#$7'#$(*$+"#$2.+#/&.-$(/$3.+.$<&--$5#$,('+#3$()$+"#$
<#5'&+#$.)3$,75-&'"#3$.'$,./+$(*$+"#$T#./$Z(/;&)4$Y/(7,$.))7.-$/#,(/+'9$!"#$,(-&01$(*$
7'#$ (*$ /.<$ 3.+.$ (/$ '.2,-#'$ <&--$ 5#$ '&2&-./$ +($ +"('#$ #:&'+&)4$ &)$ (+"#/$ 3.+.$ 5.);'8$
27'#72'$ .)3$ '0&#)+&*&0$ 0(--#0+&()'$ &)$ =(-.)3$ .)3$ (+"#/$ 0(7)+/&#'9$ !"#$ *&).-$ +#/2'$ (*$
7'#$<&--$5#$3#%#-(,#3$51$+"#$T#./$Z(/;&)4$Y/(7,$.)3$/#',()'&5-#$&)'+&+7+&()8 .*+#/$+"#$
(**&0&.-$ #'+.5-&'"2#)+$ (*$ +"#$ T#./$ Q.+.$ T.);9 $ G--$ 2#)+&()#3$ 3(#'$ )(+$ ,/#0-73#$ +"#$
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;##,&)4$5#./$'.2,-#'$*/(2$+"#$Y#)#/.-$Q&/#0+(/.+#$*(/$X)%&/()2#)+.-$=/(+#0+&()8$.)38$
&)$+"#$0.'#$(*$0(--#0+&)4$'.2,-#'$&)$.$).+&().-$ ,./;8$ .-'($ */(2$ +"#$ ,./;$ 3&/#0+(/9$!"#$
&)'+&+7+&()$0.)$".%#$.$'&)4-#$,#/2&+$.)3$+"#)$.7+"(/&J#$.$)725#/$(*$,#/'()'$*(/$+"('#$
+.';'9$N.2,-#'$'#)+$*(/$.).-1'&'$.5/(.3$)##3$+"#$LS!XN$,#/2&+$&*$'"&,,#3$(7+'&3#$XO$
@7)-#''$ +"#$ &)'+&+7+&()$ &'$ /#4&'+#/#3$ .00(/3&)4$ +($ +"#$ ./+9$ MF$ (*$ +"#$ G0+$ ()$ ).+7/#$
,/(+#0+&()B$(/$.$,#/2&+$*/(2$ +"#$ Y#)#/.-$Q&/#0+(/.+#$*(/$X)%&/()2#)+.-$=/(+#0+&()$&*$
'"&,,#3$ <&+"&)$ XO9$ [($ ,#/2&+$ &'$ /#C7&/#3$ *(/$ ;##,&)4$ 7/&)#$ .)3$ *.#0#'$ '.2,-#'$
0(--#0+#3$)()E&)%.'&%#-19$I(/#$&)*(/2.+&()$&)$G))#:$A9$
#
#
25
Implementation#of#the#Bear#Data#Bank##
!($ '722./&J#8$ +"#$ .0+&%&+&#'$ +(<./3'$ &2,-#2#)+.+&()$ (*$ +"#$ T#./$ Q.+.$ T.);$ ./#$
,/(,('#3$.'$*(--(<'?$
• !"#$ T#./$ Q.+.$ T.);$ <&--$ 5#$ 0/#.+#3$ 51$ 3#0&'&()$ (*$ +"#$ `#.3$ (*$ +"#$ Y#)#/.-$
Q&/#0+(/.+#$*(/$X)%&/()2#)+.-$=/(+#0+&()9$!"#$Q&/#0+(/$ <&--$ .,,(&)+$ +"#$ &)'+&+7+&()$
@#949$/#'#./0"$&)'+&+7+#8$).+&().-$,./;8$/#4&().-$3&/#0+(/.+#B$/#',()'&5-#$*(/$+"#$Q.+.$
T.);$.)3$.4/##$+"#$ 0()3&+&()'9$!"#$&)'+&+7+&()$/#',()'&5-#$ *(/$ +"#$T#./$Q.+.$T.);$
)##3'$+($".%#$.--$/#C7&/#3$,#/2&+'9
• !"#$/7-#'$(*$+"#$T#./$ Q.+.$T.);$<&--$5#$3#+#/2&)#3$51$+"#$Y#)#/.-$Q&/#0+(/.+#$*(/$
X)%&/()2#)+.-$=/(+#0+&()9$!"#$appointed#institution$<&--$<(/;$&)$0-('#$0((,#/.+&()$
<&+"$ +"#$ T#./$ Z(/;&)4$ Y/(7,$ .)3$ +"#$ L"&#*$ S)',#0+(/.+#$ *(/$ X)%&/()2#)+.-$
=/(+#0+&()8$ <"&0"$ &'$ /#',()'&5-#$ *(/$ +"#$ [.+&().-$ X)%&/()2#)+.-$ I()&+(/&)4$
=/(4/.22#9$$
• !"#$ (/4.)&J.+&()$ .)3$ *&-&)4$ (*$ 2()&+(/&)4$ 3.+.$ .)3$ /#,(/+'$ (*$ +"#$ T#./$ Z(/;&)4$
Y/(7,$.)3$+"#$T#./$X2#/4#)01$!#.28$.'$<#--$.'$+"#$7,3.+&)4$.)3$.32&)&'+/.+&()$(*$
3.+.5.'#'8$<&--$5#$'7,#/%&'#3$51$+"#$I#25#/$()$I()&+(/&)4$*/(2$+"#$T#./$Z(/;&)4$
Y/(7,$&)$0-('#$0((,#/.+&()$<&+"$+"#$&)'+&+7+&()$/#',()'&5-#$*(/$+"#$T#./$Q.+.$T.);9$
#
5.4. Standard#Protocols#
!"#$ ,/(+(0(-'$ ,/(,('#3$ &)$ +"&'$ '#0+&()$ ".%#$ 5##)$ ,/#,./#3$ *(/$ +"#$ ,7/,('#$ (*$ +"#$
,/#'#)+$2.).4#2#)+$,-.)9$ !"#$ 2.&)$ 4(.-'$ ./#$ +($ &2,-#2#)+$ 5#'+$ ,/.0+&0#'$ *(/$ 5#./$
&22(5&-&J.+&()$.)3$+($7)&*1$.)3$'+.)3./3&J#$+"#$,/(0#37/#'$*(/$2#.'7/&)48$2./;&)48$
'.2,-&)4$ .)3$ 3.+.$ 0(--#0+&()$ */(2$ &22(5&-&J#3$ .)3$ 3#.3$ 5#./'9$ !"#$ N+.)3./3$
=/(+(0(-'$ <&--$ *.0&-&+.+#$ 4.+"#/&)4$ &)*(/2.+&()$ /#-#%.)+$ *(/$ +"#$ 2.).4#2#)+$ (*$ +"#$
5/(<)$5#./$,(,7-.+&()8$5#./$/#'#./0"$.)3$T#./$Q.+.$T.);9$$
#
26
Immobilization#and#bear#handling#protocol#
!"#$ &22(5&-&J.+&()$ .)3$ 5#./$ ".)3-&)4$ ,/(+(0(-8$ ,/(%&3#3$ &)$ G))#:$ M8$ &'$ 3&%&3#3$ &)+($
+"/##$ ,./+'$ /#-.+#3$ +($ ',#0&*&0$ ,/(0#37/#'?$ &22(5&-&J.+&()8$ 2./;&)4$ .)3$
2#.'7/#2#)+'8$ .)3$ '.2,-&)49$ !"#$ immobilization$,/(0#37/#'$ &)0-73#$ +"#$ *(--(<&)4$
'#0+&()'?$ @AB$ +"#$ ,/(0#''$ (*$ &22(5&-&J.+&()8$ @DB$ -&*#$ '&4)$ 2()&+(/&)48$ @FB$ 4#)#/.-$
#:.2&).+&()8$ .)3$ @HB$ 5(31$ 0()3&+&()$ .''#''2#)+9$ G)$ &)+/(370+(/1$ ,./+$ 3#.-'$ <&+"$
4#)#/.-$ &)*(/2.+&()$ ()$ +"#$ /#.'()'$ *(/$ &22(5&-&J.+&()$ @/#'#./0"8$ &)>7/#3$ 5#./8$
&)+#/%#)+&()B8$-(0.+&()$.)3$3.+#8$.'$<#--$.'$+"#$).2#'$(*$+"#$,./+&0&,.)+'$.)3$3#+.&-'$()$
2#+"(3'$ .)3$ ,/(0#37/#'9$ N#0+&()$ A$ &)+/(370#'$ .$ +.5-#$ *(/$ -&'+&)4$ +"#$ '+.4#'$ (*$
&22(5&-&J.+&()$/#4./3&)4$+"#$+&2#$(*$3/74$&)>#0+&()8$ +"#$3('#8$2#+"(3$.)3$'&+#$(*$+"#$
&)>#0+&()$ .'$ <#--$ .'$ .--$ /#.0+&()'$ (*$ +"#$ 5#./$ */(2$ +"#$ 5#4&))&)4$ 7)+&-$ +"#$ #)3$ (*$
,/(0#37/#9$N#0+&()$D$.33/#''#'$ +"#$;#1$,./.2#+#/'$+".+$ )##3$+($5#$2#.'7/#3$ &)$ +"#$
&22(5&-&J#3$.)&2.-?$+#2,#/.+7/#8$"#./+$ /.+#8$/#',&/.+(/1$/.+#$.)3$(:14#)$ '.+7/.+&()9$
N#0+&()$F$/#-.+#'$+($+"#$4#)#/.-$'+.+#$(*$+"#$ 5#./$@#949$&)>7/#'8$'&4)'$(*$3&'#.'#B8$<"&-#$
N#0+&()$H$,/(%&3#'$47&3#-&)#'$+($'0(/#$+"#$0()3&+&()$(*$+"#$5#./9$
!"#$ ,./+$ ()$ marking$ 0(--#0+'$ 5.'&0$ &)*(/2.+&()$ .5(7+$ +"#$ +1,#8$ ,-.0#2#)+$ .)3$
+#0")&0.-$*#.+7/#'$(*$2./;&)4$3#%&0#'$@2&0/(0"&,8$#./$+.48$+.++((8$+#-#2#+/1$0(--./B$.)3$
+"#$ 5#./$ &)3&%&37.-$ 0(3#9$ Morphometry$ 3#'0/&5#'$ +"#$ 5(31$ 2#.'7/#2#)+'$ +($ 5#$
+.;#)9$ I#.'7/&)4$ .)3$ '.2,-&)4$ ./#$ #'+.5-&'"#3$ +($ (5+.&)$ .'$ 270"$ 3.+.$ .'$ ,(''&5-#$
4&%#)$ +".+$ +"#$ ,/(0#37/#$ (*$ 0.,+7/&)4$ .)3$ &22(5&-&J&)4$ &'$ %#/1$ &)%.'&%#9$ G$ sampling$
table$&'$,/(%&3#3$*(/$.$0()+/(-$(*$ +"#$'.2,-#'$+.;#)8$ +"#&/$)725#/'$.)3$ +"#$,-.0#'$(*$
'+(/.4#9$
#
Dead#bear#sampling#protocol##
!"#$3#.3$5#./$'.2,-&)4$,/(+(0(-$/#,/#'#)+'$.$0/70&.-$ +((-$*(/$2()&+(/&)4$ 5/(<)$5#./$
2(/+.-&+19$S+$&'$ ,/(%&3#3$&)$G))#:$P$ .)3$&+$0()'&'+'$ (*$.$general description#@&)0-73&)4$
+"#$ '&+#$ .)3$ #:.0+$ -(0.+&()B8$ general# examination8$ 3#+.&-'$ ()$ body# disposal#@#949$
,#/'()$;##,&)4$+"#$2(7)+#3$.)&2.-8$"&3#$(/$';7--B8 measuring$.)3$sampling9$!"#$,./+'$
27
()$ 4#)#/.-$ #:.2&).+&()8$ 2#.'7/&)4$ .)3$ '.2,-&)4$ ./#$ 0(22()$ +($ +"('#$ (*$ +"#$
&22(5&-&J.+&()$,/(+(0(-9$Q#+.&-#3$&)*(/2.+&()$()$"(<$+($*&--$+"#$,/(+(0(-'$&)$G))#:$A9$
!"#$'.2,-#'$0(--#0+#3$ +(4#+"#/$<&+"$+"#$ 0(//#',()3&)4$N+.)3./3$=/(+(0(-'$'"(7-3$5#$
'#)+$&)$.$/#-.+&%#$'"(/+$,#/&(3$(*$+&2#$+($+"#$T#./$Q.+.$T.);9$G$0(,1$(*$+"#$,/(+(0(-'$&'$
+($5#$'#)+$+($+"#$T#./$Z(/;&)4$Y/(7,8$<"&0"$<&--$&)*(/2$+"#$.32&)&'+/.+&()$+"/(74"$&+'$
I#25#/$ /#,/#'#)+.+&%#$ (*$ +"#$ Y#)#/.-$ Q&/#0+(/.+#$ *(/$ X)%&/()2#)+.-$ =/(+#0+&()9$
=/(%&3&)4$&)*(/2.+&()$@,/(+(0(-'B .)3$'.2,-#'$*/(2$3#.3$.)3$&22(5&-&J#3$5#./'$0(7-3$
5#$.$,/#/#C7&'&+#$ *(/$,#(,-#$.)3$&)'+&+7+&()'$ +($(5+.&)$+"#$ ,#/2&+'$*/(2$+"#$]#4&().-$
Q&/#0+(/.+#'$+($;##,$+"#$';7--8$';&)$(/$2(7)+#3$5#./$(/$+($0.,+7/#$.)&2.-'9
$
28
6.#Monitoring#program#
!"#$3#'&4)$(*$.$2()&+(/&)4$,/(4/.2$'"(7-3$&)0-73#$ 0-#./$objectives#(/$C7#'+&()'8$ +"#$
#'+.5-&'"2#)+$(*$.,,/(,/&.+#$ methods$+($.)'<#/$+"#28$ .)3$.$0()+&)7(7'$evaluation$
(*$+"#$(5>#0+&%#'$.4.&)'+$+"#$/#'7-+'$(5+.&)#39$ T#'&3#'8$#**#0+&%#$2()&+(/&)4$,/(4/.2'$
'"./#$ '(2#$ 4((3$ ".5&+'8$ '70"$ .'$ +($ 5#$ 0('+E#**#0+&%#$ @2&)&2&J#$ #:,#)'#'8$ <"&-#$
2.:&2&J&)4$3.+.$C7.-&+1B8$+($*.0&-&+.+#$ +"#$ */#C7#)+$ 7'#$(*$+"#$3.+.8$+($47./.)+##$ +"#$
.00#''&5&-&+1$(*$+"#$3.+.$+($+"#$,75-&08$+($/&4(/(7'-1$./0"&%#$+"#$3.+.8$.)3$+($,75-&'"$.)3$
/#,(/+$/#'7-+'9$!"#$-.0;$(*$,#/2.)#)+$*7)3&)48$)(+$#'+.5-&'"&)4$,(-&0&#'$(*$3.+.$7'#$.)3$
+"#$3#0#)+/.-&J.+&()$(*$2()&+(/&)4$.0+&%&+&#'$/#,/#'#)+$'&4)&*&0.)+$0()'+/.&)+'9$Z&+"(7+$
.$ /(57'+$ '1'+#2$ *(/$ 5#./$ ,(,7-.+&()$ 2()&+(/&)48$ +"#&/$ 0".)4#'$ @+/#)3'B$ <&--$ /#2.&)$
7);)(<)8$-#.%&)4$/#',()'&5-#$.7+"(/&+&#'$<&+"(7+$.$0-#./$&3#.$(*$+"#$'&+7.+&()$.)3$+"#$
,(-&0&#'$+".+$)##3$+($5#$.3(,+#39$
G2()4$+"#$-./4#$0./)&%(/#'8$ 5#./'$./#$,/(5.5-1$+"#$ 2('+$3&**&07-+$+($2()&+(/$ .'$+"#1$
./#$ )(+$ '+/&0+-1$ +#//&+(/&.-$ .)3$ 4/(7)3$ +/.0;$ '7/%#1'$ &)$ <&)+#/$ ./#$ )(+$ *#.'&5-#9$ !"#$
/#0(4)&+&()$ (*$ &)3&%&37.-$ 5#./'8$ 51$ +/.0;'$ (/$ 3&/#0+$ (5'#/%.+&()'8$ &'$ 4#)#/.--1$
&2,(''&5-#8$7)-#''$+"#1$".3$'(2#$0"./.0+#/&'+&0'$*#.+7/#'$@#949$07+$#./$ (/$+/.0;$<&+"$.$
2&''&)4$ +(#B9$ X:0#,+$ *(/$ *#2.-#'$ <&+"$ 1(7)48$ .''#''&)4$ '#:$ .)3$ .4#$ (*$ .$ 5#./$ */(2$
3&/#0+$ (5'#/%.+&()'$ &'$ )(+$ ,(''&5-#$ &)$ 2('+$ 0.'#'9$ !"#$ 2#+"(3'$ 0(22()-1$ 7'#3$ +($
2()&+(/$ 5#./$ ,(,7-.+&()'8$ <&+"$ ',#0&.-$ /#*#/#)0#$ +($ 2#+"(3'$ 7'#3$ &)$ =(-.)38$ ./#$
,/(%&3#3$&)$G))#:$A8$+(4#+"#/$<&+"$/#*#/#)0#'9$O,$+($)(<8$+"#$5/(<)$5#./$2()&+(/&)4$
3()#$ &)$ =(-.)38$ 0()370+#3$ 51$ +"#$ S)'+&+7+#$ (*$ [.+7/#$ L()'#/%.+&()$ =G[8$ ".'$ 5##)$
5.'#3$.-2('+$#:0-7'&%#-1$()$+"#$.))7.-$0(--#0+&()$(*$C7#'+&()).&/#'$*/(2$*(/#'+/1$7)&+'$
.)3$ ).+&().-$ ,./;'9$ !"&'$ 2#+"(3$ .--(<'$ &)*#//&)4$ <&+"$ /#-.+&%#$ .007/.01$ +"#$ ./#.'$ (*$
5#./$ (007//#)0#^$ "(<#%#/$ +"#$ &)+#/,/#+.+&()$ (*$ +"#$ (5'#/%.+&()'$ /#4&'+#/#3$ &)$ +"#$
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$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
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<(/-3<&3#$/#%&#<$(*$/#-#%.)+$#:,#/&#)0#9$[S[G$\,,3/.4'2#-3&)4$KHU?$AEFR9$
29
6.1.#Legal#framework#of#the#monitoring#program##
I()&+(/&)4$ (*$ +"#$ 0()'#/%.+&()$ '+.+7'$ (*$ +"#$ 5/(<)$ 5#./$ ,(,7-.+&()$ &)$ =(-.)3$ &'$ .)$
(5-&4.+&()$./&'&)4$*/(2$G/+&0-#$AA$(*$+"#$`.5&+.+'$Q&/#0+&%#$*(/$.--$',#0&#'$(*$L(227)&+1$
&)+#/#'+9$ !"&'$ ,/(%&'&()$ &'$ )(+$ /#'+/&0+#3$ +($ [.+7/.$ DVVV$ '&+#'$ .)3$ 3.+.$ )##3$ +($ 5#$
0(--#0+#3$5(+"$&)$.)3$(7+'&3#$+"#$[.+7/.$DVVV$)#+<(/;$+($.0"&#%#$.$*7--$.,,/#0&.+&()$(*$
0()'#/%.+&()$ '+.+7'9$ !"#$ .''#''2#)+$ (*$ +"#$ conservation# status$ &)$ /#-.+&()'"&,$ +($
favourable#reference#values10$".'$+($5#$/#,(/+#3$ +($+"#$X7/(,#.)$ L(22&''&()$#%#/1$
'&:$1#./'8$.00(/3&)4$+($G/+&0-#$AP$(*$+"#$3&/#0+&%#9$!"#$)#:+$).+&().-$/#,(/+'$./#$37#$51$
DVAF$@/#,(/+&)4$,#/&(3$DVVPEDVADB$.)3$DVAU$@/#,(/+&)4$,#/&(3$DVAFEDVARB9$S)$.33&+&()$
+($+"#$'7/%#&--.)0#$ (*$0()'#/%.+&()$'+.+7'8$ +"#/#$&'$.)$ #:,-&0&+$(5-&4.+&()$7)3#/$ G/+&0-#$
AD@HB$ +($ #'+.5-&'"$ .$ '1'+#2$ +($ 2()&+(/$ +"#$ &)0&3#)+.-$ 0.,+7/#$ .)3$ ;&--&)4$ @#949$ 51$ 0./$
0(--&'&()B$(*$G))#:$Se@.B$',#0&#'9$`(<#%#/8$+"#/#$&'$)($-#4.-$(5-&4.+&()$+($&)*(/2$.5(7+$
5/(<)$ 5#./'$ *(7)3$ 3#.39$ L7//#)+-18$ +"#$ L"&#*$ S)',#0+(/.+#$ (*$ X)%&/()2#)+.-$
=/(+#0+&()$&'$/#',()'&5-#$*(/$+"#$).+&().-$2()&+(/&)4$(*$',#0&#'$.)3$".5&+.+'AA9$$
#
6.2.#Goals#of#the#brown#bear#monitoring#program#in#Poland##
!"#$2.&)$4(.-$(*$+"#$2()&+(/&)4$ ,/(4/.2$ &'$ +($ provide# valuable#information#on#the#
conservation#status#of#the#brown#bear#in#Poland#and#human:bear#conflicts#as#well#as#
to# assess# the# effectiveness# of# the# measures# chosen9$ S+$ <&--$ .--(<$ ,/(%&3#$ '0&#)+&*&0E
5.'#3$#:,#/+&'#$()$ 5#./$".5&+.+$.)3$,(,7-.+&()$0()'#/%.+&()$ '+.+7'9$N,#0&*&0$4(.-'$(*$
+"#$).+&().-$2()&+(/&)4$,/(4/.2$./#$+(?$
@AB &3#)+&*1$ +"#$ ./#.$ (*$ 5#./$ (007//#)0#$ .)3$ .''#''$ 0".)4#'$ &)$ +"#$ /.)4#$ (*$
3&'+/&57+&()$(*$+"#$5/(<)$5#./$&)$=(-.)3$@'+.5-#8$3#0-&)&)48$#:,.)3&)4B^$
@DB .''#''$+"#$,(,7-.+&()$+/#)3$.)3$,/(%&3#$#'+&2.+#'$(*$+"#$)725#/$(*$5/(<)$5#./'$
&)$=(-.)3^$
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
AV$X7/(,#.)$L(22&''&()9$DVVK9$T/7''#-'8$AK$I./0"$DVVK9$QY$X)%9$TDbG]$Q@DVVHB$[(+#$+($+"#$`.5&+.+'$L(22&++##9$
G''#''2#)+8$2()&+(/&)4$.)3$/#,(/+&)4$(*$0()'#/%.+&()$'+.+7'$f$=/#,./&)4$+"#$DVVAEDVVP$/#,(/+$7)3#/$G/+&0-#$AP$(*$
+"#$`.5&+.+'$Q&/#0+&%#$@Q(0`.5EVHEVFbVF$/#%9FB9$
AA$<<<94&('94(%9,-b'&#3-&';.$
30
@FB #'+&2.+#$ +"#$ 0())#0+&%&+1$ 5#+<##)$ +"#$ <#'+#/)$ @!.+/.B$ .)3$ #.'+#/)$ @T&#'J0J.31B$
'#42#)+'$(*$+"#$5/(<)$5#./$,(,7-.+&()$&)$=(-.)3^$$
@HB ,/(%&3#$4#)#/.-$3.+.$()$ 5#./$/#,/(370+&()$#%#)+'$.)3$&3#)+&*1$ +"#$./#.'$(*$5#./$
/#,/(370+&()^$
@KB &3#)+&*1$+"#$0.7'#'$(*$5/(<)$5#./$2(/+.-&+1$.)3$+"#$./#.'$(*$"&4"#'+$2(/+.-&+1$/&';^$
@MB ,/(%&3#$3.+.$()$+"#$,(,7-.+&()$"#.-+"$'+.+7'^$$
@PB ,/(%&3#$2(/,"(-(4&0.-$3.+.$.)3$2#.'7/#2#)+'$*(/$5/(<)$5#./'$&)$=(-.)3^$
@RB ,/(%&3#$&)*(/2.+&()$()$"72.)E5#./$0()*-&0+'8$2.&)-1$()$3.2.4#'$0.7'#3$51$5#./'$
@)725#/8$ +1,#8$ +/#)3'8$ -(0.+&()B8$ .-'($ &)$ /#-.+&()$ +($ &2,-#2#)+#3$ ,/#%#)+&%#$
2#.'7/#'^$$
@UB .''#''$0".)4#'$&)$+"#$C7.-&+1$.)3$C7.)+&+1$(*$5/(<)$5#./$".5&+.+^$
@AVB &3#)+&*1$5/(<)$5#./$<&)+#/$3#))&)4$./#.'$.)3$".5&+.+^$$
@AAB #'+.5-&'"$0(22()$2()&+(/&)4$,/(+(0(-'$.)3$0((/3&).+#$+"#$ 2()&+(/&)4$ .0+&%&+&#'$
0()370+#3$51$3&**#/#)+$.32&)&'+/.+&()'8$&)'+&+7+&()'$.)3$(/4.)&J.+&()'^$$
@ADB 0/#.+#$ .$ 0#)+/.-&J#3$ Q.+.$ T.);$ <"#/#$ 2()&+(/&)4$ 3.+.$ <&--$ 5#$ 0(2,&-#3$ .)3$
'+(/#3^$
@AFB .).-1'#$'1'+#2.+&0.--1$+"#$2()&+(/&)4$3.+.$.)3$,/(370#$.$,75-&0$/#,(/+$.))7.--1^$
@AHB 0/#.+#$ .$ <#5'&+#$ <"#/#$ +"#$ 2()&+(/&)4$ /#,(/+'$ ./#$ .%.&-.5-#$ .)3$ 2()&+(/&)4$
,/(+(0(-'$0.)$5#$*&--#3$()-&)#8$.'$.$<.1$+($&)%(-%#$+"#$,75-&08$.)3^$$
@AKB 0((,#/.+#$<&+"$N-(%.;&.$.)3$O;/.&)#$&)$2()&+(/&)4$&''7#'8$+/1&)4$+($.0"&#%#$.$>(&)+$
2()&+(/&)48$.+$-#.'+$&)$+"#$g2.).4#2#)+$7)&+'h9$
$
6.3.#Description#of#the#brown#bear#monitoring#program$
!"#$ ,/(,('#3$ 2()&+(/&)4$ '0"#2#$ *(/$ +"#$ 5/(<)$ 5#./$ &)$ =(-.)3$ &'$ .)$ adaptive$
2()&+(/&)48$&9#98$0.)$5#$2(3&*&#3$&)$/#',()'#$+($)#<$'&+7.+&()'$(/$C7#'+&()'$.)3$7,()$
>7'+&*&0.+&()9$ G)$ &2,(/+.)+$ ,./+$ (*$ +"#$ ,/(4/.2$ <&--$ 5#$ +"#$ ,/(370+&()$ (*$ annual$
reports$ '722./&J&)4$ +"#$ 2()&+(/&)4$ 3.+.9$ !"#'#$ /#,(/+'$ <&--$ 5#$ ,75-&'"#3$ &)$ +"#$
31
official$website$ 3#3&0.+#3$ +($ 5/(<)$ 5#./$ &''7#'$ .)3$ 2()&+(/&)4$ &)$ =(-.)39$ !"#$
2()&+(/&)4$ ,/(4/.2$ '"(7-3$ .-'($ &)%(-%#$ +"#$ public9$ !"#$ ,#/'()$ /#',()'&5-#$ +($ ,7'"$
*(/<./3$.)3$0((/3&).+#$+"#$ 2()&+(/&)4$,/(4/.2$&'$+"#$Member# on# Monitoring$*/(2$
+"#$T#./$Z(/;&)4$Y/(7,8$<&+"$+"#$'7,,(/+$(*$+"#$Y/(7,$.)3$+"#$Y#)#/.-$Q&/#0+(/.+#$(*$
X)%&/()2#)+.-$=/(+#0+&()9$I(/#$&)*(/2.+&()$&'$,/(%&3#3$&)$G))#:$A9$
!"#$ ,/(,('#3$ 2()&+(/&)4$ ,/(4/.2$ 0()'&'+'$ (*$ .$ continuous# baseline# monitoring8$
,.''&%#8$/.+"#/$0/73#$.)3$&)#:,#)'&%#8$.)3$.$periodical#intense#monitoring8$.0+&%#$.)3$
#:,#)'&%#8$ +".+$ <&--$ ,/(%&3#$ ,/#0&'#$ &)*(/2.+&()$ 5.'#3$ ()$ 4#)#+&0$ .)3$ ".5&+.+$
2()&+(/&)4$ ,#/&(3&0.--19$ !"#$ ,./.2#+#/'$ +($ 5#$ 2()&+(/#3$ &)0-73#$ 5/(<)$ 5#./$
3&'+/&57+&()8$.57)3.)0#8$/#,/(370+&()$.)3$2(/+.-&+18$<&)+#/$3#)'8$ ,(,7-.+&()$ +/#)3'8$
".5&+.+$ .)3$ "72.)E5#./$ 0()*-&0+'9$ !"#$ 2()&+(/&)4$ ,/(4/.2$ '"(7-3$ .-'($ <(/;$ ()$
3#%#-(,&)4$ g*.%(7/.5-#$ /#*#/#)0#$ %.-7#'h$ +($ 5#$ /#.0"#3$ .)3$ +($ 2()&+(/$ .4.&)'+$ +"#$
(5>#0+&%#'9$ Y&%#)$ &+'$ *-#:&5-#$ 0"./.0+#/8$ +"#$ ,/(4/.2$ .-'($ 2.1$ &)0-73#$ ad:hoc#
monitoring$.0+&%&+&#'8$*(07'#3$()$.$ ',#0&.-$+./4#+9$_(/$ +"#$07//#)+$'&+7.+&()$&)$=(-.)38$
.$'&:E,/()4#3$'1'+#2$&'$/#0(22#)3#3?$
$
Baseline#monitoring#
(a) Annual#survey#through#questionnaires#
S)*(/2.+&()$()$5/(<)$5#./$3&'+/&57+&()8$/#,/(370+&()$#%#)+'$.'$<#--$.'$3#))&)4$.)3$
/#,/(370+&()$./#.'$<&--$5#$(5+.&)#3$+"/(74"$.))7.-$C7#'+&()).&/#'9$!"#$C7#'+&()).&/#$
'"(7-3$ 5#$ ;#,+$ '&2,-#$ @'##$ ,/(,('.-$ &)$ G))#:$ RB9$ \)-1$ 0()*&/2#3$ .)3$ /#-&.5-#$ 5#./$
/#0(/3'$ '"(7-3$ 5#$ 0()'&3#/#38$ #',#0&.--1$ &)$ ./#.'$ (*$ ',(/.3&0$ 5#./$ (007//#)0#9$
G++#)+&()$'"(7-3$5#$,7+$&)$+"#$/#0(/3'$(*$*#2.-#'$<&+"$1(7)4$.)3$+"#&/$<&)+#/$3#)'$
.)3$&)$/#0(/3'$*/(2$+"#$/#4&()'$(*$T#';&3$Ni3#0;&$.)3$T#';&3$[&';&8$<"&0"$2.1$'#/%#$.'$
0())#0+&()$ 5#+<##)$ +"#$ 2.&)$ 5#./$ /#,/(370+&%#$ )70-#&$ (*$ !.+/.$.)3$T&#'J0J.319$ !"#$
C7#'+&()).&/#'$'"(7-3$5#$'#)+$+($+"#$_(/#'+/1$G32&)&'+/.+&()8$[.+&().-$=./;'8$"7)+&)4$
7)&+'8$]#4&().-$Q&/#0+(/.+#'$*(/$X)%&/()2#)+.-$=/(+#0+&()8$/#'#./0"#/'$.)3$[Y\'$+($5#$
*&--#3$ +"/(74"(7+$ +"#$ 1#./$ @!.5-#'$ F$ .)3$ H8$ '##$ G))#:$ U$ *(/$ .$ ,(+#)+&.-$ -&'+B9$ S+$ &'$
/#0(22#)3#3$+".+$/#',()3#)+'$0(2,-#+#$+"#$C7#'+&()).&/#'$.'$'(()$.'$.$5#./$/#0(/3$
&'$ 4.+"#/#39$ !"#$ C7#'+&()).&/#'$ '"(7-3$ 5#$ .-'($ .%.&-.5-#$ *(/$ +"#$ ,75-&0$ +"/(74"$ +"#$
32
(**&0&.-$5#./$<#5'&+#9$ !"#$.))7.-$/#,(/+$'722./&J&)4$+"#$/#'7-+'$*/(2$ +"#$2()&+(/&)4$
3.+.$ '"(7-3$ 5#$ '#)+$ +($ +"#$ /#',()3#)+'$ .)3$ ,75-&'"#3$ &)$ +"#$ <#5'&+#9$ S+$ &'$ "&4"-1$
/#0(22#)3#3$ +($ <(/;$ (7+$ '(2#$ (5'#/%.+&()$ &)3#:8$ #**(/+E0(//#0+#3$ .)3$ %.-&3.+#$ &+$
<&+"$&)3#,#)3#)+$.)3$2(/#$,/#0&'#$2#+"(3'AD9$
(b) Register#of#dead#bears#
Q.+.$ */(2$ 3#.3$ .)&2.-'$ ./#$ (*$ (7+'+.)3&)4$ &2,(/+.)0#$ *(/$ 2()&+(/&)4$ .)1$
,(,7-.+&()AF$.)38$&)$+"#$0.'#$(*$5/(<)$5#./'$+"#&/$/#4&'+/.+&()$&'$.$-#4.-$(5-&4.+&()9$!"#$
]#4&().-$ Q&/#0+(/.+#'$ *(/$ X)%&/()2#)+.-$ =/(+#0+&()$ ,-.1$ .$ ;#1$ /(-#$ &)$ .00(2,-&'"&)4$
+"#$ 3&**&07-+$ +.';$ (*$ 0(2,&-&)4$ .--$ &)*(/2.+&()$ */(2$ 3#.3$ 5#./'$ .)3$ &)$ #)0(7/.4&)4$
"7)+#/'8$/#'#./0"#'$.)3$,#(,-#$<(/;&)4$&)$+"#$*&#-3$+($0()+/&57+#$+($+"&'$/#4&'+#/$<&+"&)$
+"#$ Q.+.$ T.);9$ X.0"$ +&2#$ .$ 5#./$ &'$ *(7)3$ 3#.38$ &+$ &'$ )#0#''./1$ +($ &)*(/2$ +"#$
0(//#',()3&)4$ ]#4&().-$ Q&/#0+(/.+#$ *(/$ X)%&/()2#)+.-$ ,/(+#0+&()9$ S)*(/2.+&()$ .)3$
'.2,-#'$'"(7-3$5#$0(--#0+#3$.00(/3&)4$+($+"#$,/(+(0(-$*(/$3#.3$5#./'$.)3$'#)3$+($+"#$
Q.+.$ T.);9$ N.2,-#'$ */(2$ 3#.3$ 5#./'$ <&--$ 5#$ ,#/&(3&0.--1$ .).-1'#3$ 7)3#/$ +"#$
*/.2#<(/;$(*$+"#$4#)#+&0$2()&+(/&)4$(/$7,()$)##3$(/$/#C7#'+$(*$&)+#/#'+#3$4/(7,'9$S+$
&'$/#0(22#)3#3$+".+$+"#$/#4&'+#/$<&--$+/1$+($4.+"#/$&)*(/2.+&()$.5(7+$+"#$5#./$3#.+"'$
(007//&)4$&)$,.'+$1#./'9$$
(c) Monitoring#conflicts#and#damages##
Q.2.4#'$0.7'#3$51$5/(<)$5#./'$(7+'&3#$[.+&().-$=./;'$./#$<#--$&)%#)+(/&#3$51$+"#$
]#4&().-$Q&/#0+(/.+#'$(*$X)%&/()2#)+.-$=/(+#0+&()$&)$]J#'Jj<8$W.+(<&0#$.)3$W/.;j<9$
!"#$ 4(.-$ "#/#$ <&--$ 5#$ +($ ,/(370#$ '1'+#2.+&0.--1$ .$ >(&)+$ .))7.-$ /#,(/+$ <&+"$ +"#$
&)*(/2.+&()$*/(2$+"#$]#4&().-$Q&/#0+(/.+#'$.)3$[.+&().-$=./;'$+".+$<&--$'722./&J#$.--$
5#./$ 3.2.4#'$ &)$ =(-.)3$ .)3$ +".+$ <&--$ 5#$ ,./+$ (*$ +"#$ .))7.-$ 2()&+(/&)4$ /#,(/+9$ S+$ &'$
"&4"-1$ /#0(22#)3#3$ +($ &)0-73#$ &)$ +"#$ *&#-3$ ,/(+(0(-'$ .)3$ 3.2.4#$ 3.+.5.'#$ +"#$
4#(4/.,"&0.-$ 0((/3&).+#'8$ 3&'+&)47&'"$ +"#$ 3.+#'$ (*$ 3.2.4#$ */(2$ 3.+#$ (*$ &)',#0+&()8$
0(--#0+&)4$".&/$'.2,-#'$<"#)$.%.&-.5-#$.)3$+/.)'*#//&)4$+($+"#$Q.+.$T.);8$.)3$,/(%&3#$
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
AD$W&)35#/4$c98$X/&0''()$Y9$d N<#)'()$c9X9$DVVU9$I()&+(/&)4$/./#$(/$#-7'&%#$-./4#$2.22.-'$7'&)4$#**(/+E0(//#0+#3$
%(-7)+./1$(5'#/%#/'9$T&(-(4&0.-$L()'#/%.+&()$AHD?$AKUEAMK9$
AF$T/#&+#)2('#/$O98$T/#&+#)2('#/EZk/'+#)$L"98$e()$G/:$I98$l&22#/2.))$_98$]1'#/$G98$G)4'+$L"98$I(-&)./&Ec(5&)$G98$
I(-&)./&$=98$a&))#--$c98$N&#4#)+".-#/$G9$d Z#5#/$c9EI9$DVVM9$Y7&3#-&)#'$*(/$+"#$I()&+(/&)4$(*$a1):9$W(/.$T#/&0"+$[/9$
FF#8$I7/&8$N<&+J#/-.)39$
33
&)*(/2.+&()$ .5(7+$ +"#$ ,/#%#)+&()$ 2#+"(3'$ 7'#3$ <"#)$ +"#$ 3.2.4#$ ".,,#)#39$
S)*(/2.+&()$.5(7+$(+"#/$"72.)E5#./$0()*-&0+'$'"(7-3$5#$'&2&-./-1$4.+"#/#39$$
$
!.5-#$F9$N722./1$(*$+"#$3&**#/#)+$'+.4#'8$+.';'$.)3$+&2#*/.2#$*(/$+"#$3&**#/#)+$
5/.)0"#'$(*$+"#$5/(<)$5#./$2()&+(/&)4$,/(4/.2$&)$=(-.)3$$
Monitoring#type#
Stages#and#tasks#
Timeframe#
Z#5'&+#$
L/#.+&()$
Z(/;&)4b2.&)+#).)0#$
DVAD$
DVADEDVAR$
G))7.-$/#,(/+$
$
DVADEDVAR$@c7-1BA$
BASELINE#MONITORING$@0()+&)7(7'8$#%#/1$1#./B$
m7#'+&()).&/#'$'7/%#1'$
L&/07-.+#$d$0(--#0+$C7#'+&()).&/#'$(*$,/#%&(7'$1#./$
DVADEDVAR$@c.)E_#5B$
$
Q.+.5.'#$&),7+$
DVADEDVAR$@I./EG,/B$
$
Q.+.$.).-1'&'$d$/#,(/+$,/#,./.+&()$
DVADEDVAR$@I.1Ec7)B$
$
N#)3$/#,(/+$,/#%&(7'$1#./$
DVADEDVAR$@c7-1BA$
Q#.3$5#./'$
Q.+.$./0"&%#$
DVADEDVAR$
$
Y#)#+&0$.).-1'&'$
DVAPEDVAR$
$
\+"#/$.).-1'&'$
O,()$/#C7#'+$
$
]#,(/+$
DVAPEDVAR$@c7-1BA$
Q.2.4#$2()&+(/&)4$
_&#-3$&)',#0+&()$d$'.2,-#$0(--#0+&()$
DVADEDVAR$
$
c(&)+$3.+.5.'#$d$/#,(/+$
DVADEDVAR$@c7-1BA$
INTENSIVE#MONITORING$@,#/&(3&0.-8$#%#/1$MEAV$1#./'B$
Y#)#+&0$2()&+(/&)4$
N.2,-#$0(--#0+&()$
DVAP$
$
a.5(/.+(/1$.).-1'&'$
DVAR$
$
Q.+.$.).-1'&'$d$/#,(/+$
DVAR$
[.+&().-$,/#'#)0#$'7/%#1'$
Q#'&4)8$,/#,./.+&()$(*$,/(+(0(-'8$#:,-.).+(/1$
<(/;'"(,'8$*&#-3$<(/;8$5-(4$0/#.+&()$
DVAF$
$
Q.+.5.'#$0/#.+&()8$3.+.$.).-1'&'8$/#,(/+$
DVAH$
`.5&+.+$2()&+(/&)4$
_/.42#)+.+&()$.).-1'&'$
DVAFEAH$
$
`.5&+.+$2(3#-$57&-3&)4$
DVAH$
$
]#4&'+#/$".5&+.+$3#+#/&(/.+&()$,(&)+'$
DVAF$8$37/&)4$(+"#/$
*&#-3$.0+&%&+&#'$
AD#HOC#MONITORING$@<"#)$)##3#3B$
L())#0+&%&+1$'+731$!.+/.E
T&#'J0J.31$$
T#./$,/#'#)0#$'7/%#1$.)3$4#)#+&0$2()&+(/&)4$
DVAFEDVAH$
AL(&)0&3&)4$<&+"$+"#$T#./$Z(/;&)4$4/(7,$.))7.-$/#,(/+$
34
Intensive#monitoring#
(d) Genetic#monitoring##
[(<.3.1'8$ +"#$ 2('+$ /#-&.5-#$ 2#+"(3$ +($ (5+.&)$ #'+&2.+#'$ (*$ 5#./$ )725#/'$ .)3$
,(,7-.+&()$+/#)3'$&'$ 4#)#+&0$2()&+(/&)49$!"&'$2#+"(3$ 2.1$.-'($,/(%&3#$%.-7.5-#$ 3.+.$
()$ +"#$ 4#)#+&0$ 0())#0+&%&+1$ 5#+<##)$ +"#$ <#'+#/)$ @!.+/.B$ .)3$ #.'+#/)$ @T&#'J0J.31B$
'#42#)+'$(*$+"#$5#./$,(,7-.+&()9$G$0(2,-#+#$4#)#+&0$2()&+(/&)4$2.1$/#C7&/#$.5(7+$
+<($1#./'8$+"#$*&/'+$*(/$sampling$@3#'&4)8$,#/2&+'8$0(--#0+&()8$3.+.5.'#B$.)3$+"#$'#0()3$
*(/$analysis$@4#)#+&0$.)3$'+.+&'+&0.-B$.)3$,/#,./.+&()$(*$+"#$/#,(/+9$S+$'"(7-3$0(%#/$+"#$
./#.$ (*$ 5#./$ 3&'+/&57+&()$ (5+.&)#3$ */(2$ +"#$ C7#'+&()).&/#$ '7/%#1'9$ !"#$ ./#.'$ (*$
,#/2.)#)+$ 5#./$ (007//#)0#$ @!.+/.8$ T&#'J0J.318$ T#';&3$ n-i';&$ .)3$ l1<&#0;&B$ 0.)$ 5#$
'.2,-#3$ &)+#)'&%#-1$ &)$ .$ 2(/#$ '1'+#2.+&0$ <.1$ *(/$ .$ '"(/+$ ,#/&(3$ @#949$ +"#$ .7+72)$
2()+"'B9$ `(<#%#/8$ +"#$ ./#.'$ (*$ +#2,(/.-$ 5#./$ (007//#)0#$ @T#';&3$ Ni3#0;&8$ T#';&3$
[&';&8$ T.5&.$ Yj/.8$ Y(/0#8$ =&#)&)18$ N,&'JB$ 2.1$ 5#$ '.2,-#3$ (,,(/+7)&'+&0.--1$ .)3$ *(/$
-()4#/$,#/&(3'$@#949$+"#$<"(-#$ 1#./B9$ G'$&+$&'$%#/1$3#2.)3&)4$&)$ +#/2'$ (*$+&2#8$#**(/+$
.)3$2()#18$4#)#+&0$2()&+(/&)4$2.1$5#$/#,#.+#3$every#6#years8$+($'1)0"/()&J#$&+$<&+"$
+"#$ /#,(/+$ ()$ +"#$ 5/(<)$ 5#./$ 0()'#/%.+&()$ '+.+7'$ *(/$ +"#$ X7/(,#.)$ L(22&''&()$
@!.5-#'$F8$H$.)3$KB9$!"#$DVAF$/#,(/+$*(/$ XL$ <&--$ &)0-73#$ +"#$ /#'7-+'$ */(2$ +"#$,/#'#)+$
2.).4#2#)+$,-.)9$!"#$)#:+$4#)#+&0$2()&+(/&)4$'"(7-3$5#$0()370+#3$&)$DVAPEDVAR$.)3$
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38
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Ecological# corridors.# Critical# points# to# maintain# habitat# connectivity# in#
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45
!
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!
Fig.!4.!Ecological!corridors!and!critical!points!(current!and!potential)!in!the!Polish!Carpathians.!
46
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47
!
!
!
!
Fig.!5.!Unfragmented!areas!in!the!Polish!Carpathians,!identified!as!those!further!than!500!m!from!the!closest!road!or!trail.!The!unfragmented!
areas!smaller!than!4!km2!are!marked!in!yellow;!the!“secure!habitat!areas”!for!brown!bears,!larger!than!4!km2,!are!marked!in!green.!
!
!
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10.$Annex$
Annex$1.$ Status,'ecology'and'management'of'the'brown'bear'in'Poland'(“full'version”'
of'the'brown'bear'management'plan'for'Poland).'
Annex$ 2.'List'of' participants'in'the'workshops' for'the'preparation' of' the'brown'bear'
management' plan' conducted' in' Kraków' in' 8D9' November' 2010,' 27D28' January' 2011'
and'20D22'February'2011.'
Annex$ 3.' Program' of' the' I' and' II' workshops' devoted' to' the' preparation' of' the'
management'plan'for'the'brown'bear'in'Poland'"Monitoring'and'solving'conflicts".'
Annex$ 4.' Program' of' the' I' and' II' workshops' devoted' to' the' preparation' of' the'
management'plan'for'the'brown'bear'in'Poland'"Protecting'brown'bear'habitat”.'
Annex$ 5.$ Program' of' I' International' Workshop' devoted' to' the' preparation' of' the'
management'plan'for'the'brown'bear'and'other'large'carnivores'in'Poland'“Managing'
transboundary' populations' of' brown' bear' and' other' large' carnivores' in' the'
Carpathians”.'
Annex$6.'Protocols'for'brown'bear'immobilization'and'sampling.'
Annex$7.'Protocols'for'sampling'dead'brown'bears.'
Annex$8.'Proposed'monitoring'protocol'for'the'questionnaire'surveys.'
Annex$9.'Network'of'potential'respondents'to'the'questionnaire'surveys.'
81
... three million per year), but human activities are restricted to designated areas and trails, and no artificial feeding is conducted [50]. The habitat of Tatra Mts supports brown bear occurrence, reproduction and movement and the number of bears inhabiting the area has been estimated in 45-79 individuals [51,52]. ...
... Numerous target and non-target species use this human-provided food intended for ungulates [58], and brown bear movement in the area is significantly affected by feeding practices [41]. Brown bears inhabiting the area are estimated at 46-61 individuals and belong to the eastern Carpathian subpopulation [51]. ...
... With summer progressing, the food intake increases markedly (hyperphagia; [67]) until the bears gain enough body mass before denning [25]. Denning takes place mostly from November to April in Tatra mountains [51], whereas in Bieszczady, some bears are active during winter, partly due to artificial feeding [66]. Thus, samples span the active period, which allow us to examine temporal patterns in the nutritional quality of bear diets. ...
Losing seasonal patterns in a hibernating omnivore? Diet quality proxies and faecal cortisol metabolites in brown bears in areas with and without artificial feeding
Article
Full-text available
Bears are omnivores particularly well-adapted to variations in the nutritional composition, quality and availability of food resources. Artificial feeding practices have been shown to strongly influence diet composition and seasonality, as well as to cause alterations in wintering and movement in brown bears (Ursus arctos). In this study, we investigated seasonal differences (hypophagia vs hyperphagia) in food quality of two brown bear subpopulations in the Polish Carpathians using faecal nitrogen (FN) and carbon (FC) estimates. The subpopu-lations inhabit areas that differ in artificial feeding practices: no artificial feeding occurs in the western subpopulation (Tatra Mountains), while artificial food targeted to ungulates is provided and used year-round in the eastern subpopulation (Bieszczady Mountains). We also compared these results with faecal cortisol metabolites (FCM) to explore how FN and FC correlate with the hypothalamic-pituitary-adrenal axis activity and if the seasonal patterns are apparent. We found that in Tatra Mts bears fed on significantly higher quality diet, as shown by FN and FC values, and had significantly higher FC levels in hyperphagia, when they accumulate fat reserves for wintering. The pattern in FCM levels for Tatra subpopula-tion followed the changes in energy intake during the seasons of hypo-and hyperphagia, while in Bieszczady Mts, the area with intensive feeding, no seasonal patterns could be observed. Artificial feeding practices may disrupt nutrient phenology and seasonality, relative to subpopulations with natural diets. We showed that the availability of human-provided foods may alter not only the overall dietary quality, but also hormonal patterns linked to seasonal nutritional requirements. Combining FN, FC and FCM proved to be a useful tool for reconstructing diet quality and related physiological patterns.
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... The Carpathian brown bear population is the second largest in Europe and extends over six countries. It is divided into three population segments; the connectivity between the western and eastern segments is quite limited (Selva et al., 2011;Straka et al., 2012). Infrastructure development is considered the main threat for the persistence of this population; the lack of transboundary cooperation in management has also been pointed as an issue (Selva et al., 2011). ...
... It is divided into three population segments; the connectivity between the western and eastern segments is quite limited (Selva et al., 2011;Straka et al., 2012). Infrastructure development is considered the main threat for the persistence of this population; the lack of transboundary cooperation in management has also been pointed as an issue (Selva et al., 2011). The brown bear population in the Tatra Mountains represents the core area of the western segment of the Carpathian population and it is split between Poland and Slovakia. ...
... Our bear movement data emphasises the potentially important role of subadult males in connecting bear subpopulations. Iwo's dispersal shows that the western and eastern population segments in the Carpathians, genetically differentiated after a century of isolation (Straka et al., 2012), may maintain connectivity, although not necessarily through the corridor derived from movement models (Zi ołkowska et al., 2016), which is the shortest route and was proposed as a target for conservation actions (Selva et al., 2011). The presented case of bear dispersal confirms the importance of road wildlife passages in supporting species movements (Fig. A.4). ...
Bears without borders: Long-distance movement in human-dominated landscapes
Article
Full-text available
  • Jan 2019
Conservation of wide-ranging species and their mobility is a major challenge in an increasingly fragmented world. Species are traditionally viewed as static conservation targets and the importance of securing long-distance movement of individuals is still underappreciated in conservation and policy. Here, we investigated large carnivore movements in humanized landscapes of Europe. We describe the movement of 6 GPS-tracked male brown bears, including one of the longest dispersal events recorded in this species. We looked at the relationships of bear movement paths with country borders, roads, built-up areas and habitat composition. The daily distance of resident individuals was 5.5 ± 4.4 km and almost twice as long in the dispersing subadult (9.3 ± 6.4 km). Maximum displacement of the disperser was 360 km (compared to 43.3 ± 13.0 km in resident bears). The resident bears moved within less than 10 km to built-up areas, while the dispersing bear stayed mostly at larger distances. The bears also frequently crossed roads (0–31 per month) and state borders (0–14 per month). The dispersing bear moved through four countries. A review of 29 cases and studies of large carnivore long-distance movements in Europe showed that transboundary movement represented over 96% of all cases; 9 extended over different populations and 10 over recolonization areas. Most documented cases of long-distance dispersal (52% of 21 individual cases) ended with the death of the animal (82% of confirmed deaths were human-caused, 46% were legal killings) before it could reproduce. Reproduction was documented only in 2 of the individual cases. We emphasize high conservation value of long-distance dispersers in large carnivore populations and the need to reevaluate how they are viewed and managed. We urge to consider wide-ranging, transboundary movements in conservation policies.
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... The third area of permanent bear presence and occasional reproduction is Beskid Żywiecki. The connectivity between the western and eastern segments seems to be limited (Selva et al. 2011). Due to objective reasons (conservation activities allowing longterm monitoring of brown bear mortality), the sampling mostly focused on the Tatra National Park. ...
... The forest is intertwined with meadows, particularly in the lower parts of the mountains, and represents a suitable habitat for the brown bear (Fernández et al. 2012;Ziółkowska et al. 2016). Brown bears inhabiting the area are estimated at 46-61 individuals and belong to the eastern Carpathian subpopulation (Selva et al. 2011). The current total population size estimate in the Polish Carpathians is 99-166 individuals (EC 2019). ...
90Sr and stable element levels in bones of brown bears: long-term trends in bear populations from Croatia and Poland
Article
Full-text available
  • Dec 2022
  • ENVIRON SCI POLLUT R
The aim of this study was to investigate the temporal trends and geographical differences in 90Sr and stable element (Ba, Ca, Mn, Sr, Pb, Zn) levels in the bones of Croatian and Polish brown bear (Ursus arctos) populations. Experimental data suggest that in the decades after nuclear weapon tests and the Chernobyl accident, 90Sr bone activity concentrations decreased from 352 to 11 Bq kg-1 in the Croatian bear population (period 1982-2015) and from 831 to 27 Bq kg-1 in Polish bears (period 1962-2020). Calculated effective and ecological half-lives were 9 and 13 years for Croatian bears, and 15 and 31 years for Polish bears, respectively. Different temporal trends were noted in levels of Ba, Mn, Pb and Zn between the two countries with majority of bones having lower Pb, Sr and Zn in Croatian than in Polish bears. Estimated values for the soil-to-bear transfer of 90Sr were the same order of magnitude in the studied populations. Contrary to this, the estimated transfer of stable Sr was an order of magnitude lower for the Croatian bear population compared to Polish bears. The observed differences in soil-to-bear transfer between stable Sr and 90Sr found for Croatian bears might suggest the need for careful consideration on the use of stable Sr data as an analogue for 90Sr. To our knowledge, this is the first study that analysed 90Sr activity in tissue of brown bears. As such, it provides insight into the fate and behaviour of one of the most relevant anthropogenic radionuclides at the top of the food chain.
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... To date, MTBC infection has only been detected twice in free-living bear species: An American black bear (Ursus americanus) and a Marsican brown bear (Ursus arctos marsicanus; Bruning-Fann et al. 2001; Fico et al. 2019). Poland is home to a brown bear population of approximately 110 individuals confined to the Carpathians, with most of the population inhabiting its easternmost part, the Bieszczady Mountains(Selva et al. 2011;Ś mietana et al. 2014). The species is strictly protected in the European Union under the Habitats Directive ...
Detection of Mycobacterium tuberculosis Complex Genetic Material in a Free-Living Brown Bear (Ursus arctos)
Article
  • Jun 2023
  • J WILDLIFE DIS
Mycobacterium tuberculosis complex (MTBC) has rarely been detected in bears (Ursidae). We describe detection of MTBC genetic material using a single-tube, high-multiplex PCR and fluorescence-based detection system in a throat swab collected from a free-living, problem individual during immobilization and telemetry collar deployment. Mycobacterial culture was negative in all samples.
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... It only can complement data on the area of occurrence (e.g. Selva et al. 2011). -·Accuracy and precision: inaccurate. ...
Guidance on estimation of abundance and density of wild carnivore population:methods, challenges, possibilities
Article
Full-text available
  • Nov 2020
This guidance reviews the methods for estimating relative abundance and density in nine large European wild carnivore species, somerepresenting relevant health concerns andprovides insights on how to obtain reliable estimations by using those methods. On a local scale, the appropriate method should take into accountthe characteristics of the study area, the estimated survey efforts, the expected results (i.e. a measure of true density or just an index of abundance to monitor the trend in space and time) the level of accuracy and precision, and a proper design so to obtain a correct interpretation of the data. Among all methods, the camera trapping (CT) methods, especially those recently developed, are the most promising for the collection of robust data and can be conducted in a wide range of species, habitats, seasons and densities with minimal adjustments. Some recently developed CT methods do not require individual recognition of the animals and are a good compromise of cost, effort and accuracy. Linear transects,particularly Kilometric Abundance Index (KAI) is applicable for monitoring large regions.A large challenge is compiling and validating abundance data at different spatial scales. Based on ENETWILD initiative, we recommend developing a permanent network and a data platform to collect and share local density estimates, so as abundance in the EU, which would enable to validate predictions for larger areas by modelling. It would allow to identify gaps in the data on wild carnivores (including the species not assessed in the present report) and to focus on these areas for improving predictions. This platform must facilitate the reporting by wildlife policy makers and relevant stakeholders, but also citizen science initiatives.Also, there is need to improve the reliability of local density estimations by developing practical research on methods able to derive densities in untested species and situations, making the application of methods easier for local teams.
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Population dynamics and spatial distribution of large carnivores in the Ukrainian Carpathians and Polissya
Article
Full-text available
  • Jan 2023
Large carnivores play an important role as indicators of the state of the natural ecosystems. The analysis of the number and distribution of large carnivores (brown bear – Ursos arctos, Eurasian lynx – Lynx lynx and grey wolf – Canis lupus) was established in the Ukrainian Carpathians and Ukrainian Polissya. Annual data on the number of large carnivores on the territories of hunting units and nature conservation areas from 2009 to 2019 was summarized. To analyze the number and distribution of largecarnivores in the Ukrainian Carpathians, data from 4 regions were taken into account, namely Lviv, Zakarpattia, Ivano-Frankivsk and Chernivtsi regions. To analyze the number and distribution of large carnivores in Ukrainian Polissya, data from 6 regions were taken into account – Volyn, Rivne, Zhytomyr, Kyiv, Chernihiv and Sumy regions. According to official data obtained from hun-ting units and nature conservation areas in 2019, there were 375 bears, 435 lynxes and 563 wolves in the Ukrainian Carpathians; and 4 bears, 128 lynxes and 609 wolves in Ukrainian Polissya. Based on the collected data, the maps of the distribution of large carnivores in the Ukrainian Carpathians and Ukrainian Polissya were created in the format of a grid of squares of 10 by 10 km (cell size 100 km²), namely – density maps of populations of large carnivores, as well as maps of forest habitats of large carnivores. The obtained results provided a better understanding of the dynamics of large carnivores over the last decade in terms of regions, as well as the density of populations of large carnivores in certain areas and their distribution areas in the Ukrainian Carpathians and Ukrainian Polissya. However, the summary results of the number of individuals obtained based on official reports of hunting units and nature conservation areas are overestimated due to the problem of "double" accounting of animals by users of adjacent lands (hunting units, nature conservation areas). Therefore, it is important to establish synchronization of accounting between users of adjacent lands (nature protection areas, forestries, etc.), to use unified research methods, and to exchange monitoring data and information between institutions of different state subordination. Such scientifically based data are the basis for the development and implementation of measures for the conservation and management of large carnivore populations at the regional, national and international levels.
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Brown Bear ( Ursus arctos ; Eurasia)
Chapter
  • Nov 2020
Bears have fascinated people since ancient times. The relationship between bears and humans dates back thousands of years, during which time we have also competed with bears for shelter and food. In modern times, bears have come under pressure through encroachment on their habitats, climate change, and illegal trade in their body parts, including the Asian bear bile market. The IUCN lists six bears as vulnerable or endangered, and even the least concern species, such as the brown bear, are at risk of extirpation in certain countries. The poaching and international trade of these most threatened populations are prohibited, but still ongoing. Covering all bears species worldwide, this beautifully illustrated volume brings together the contributions of 200 international bear experts on the ecology, conservation status, and management of the Ursidae family. It reveals the fascinating long history of interactions between humans and bears and the threats affecting these charismatic species.
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A dispersing bear in Białowieża Forest raises important ecological and conservation management questions for the central European lowlands
Article
Full-text available
  • Jul 2020
In Europe brown bears are currently largely confined to mountainous areas and eastern European refugia with sparse human populations. Poland typifies this distribution, with bears being present in the Carpathian Mountains, but absent from the lowlands. Recently large carnivore populations have been recovering throughout Europe, raising the question of the potential for bears to recolonize both the Polish and wider central European lowlands. The nearest population with good connectivity to the Polish lowlands is in central Belarus, where bears are currently expanding. In recent years there have been at least two undocumented sightings of bears in eastern Poland, such as in Białowieża Forest in 2010 and Augustów Forest in 2018. While carrying out a camera trap study in June 2019, we documented the first brown bear in the Polish part of Białowieża Forest since 1963. The individual apparently left for the Belarusian side of the forest, where a bear continued to be spotted several times over the following month. After over half a year of no signs of bears, on the 1st April 2020, a bear was recorded again on the Belarusian side of the forest. It is unknown whether this was the same individual. If the brown bear population in Belarus continues to expand, such visits of bears to eastern Poland are likely to become increasingly frequent in the near future. This could lead to the eventual reestablishment of the species in Białowieża Forest and the wider central European lowlands, restoring a diverse array of ecological interactions, while having significant and complex management implications. We briefly review the ecosystem impacts of bears in their natural ranges and discuss potential conservation management issues that would need to be dealt with in order to minimise potential conflicts, honour legal obligations and conserve the species.
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Warsztaty terenowe w Tatrzańskim Parku Narodowym – zagadnienia problemowe (How to resolve conservation problems in the Tatra National Park - summary of findings from a workshop).
Chapter
  • Oct 2018
Field workshop in the Tatra National Park (TPN) was the second part of the conference on strict protection in nature reserves and national parks. The first day was held in the Kościeliska valley, and the second day, in the Jaworzynka valley. During the first day the participants had an opportunity to become familiar with practical issues related to nature conservation, to share their own experiences, and to discuss possible solutions to the recognized problems. One of the most important environmental issues in this part of the Tatra mountains is an extensive wind disturbance that had taken place several years ago. Some of the participants believed that this disturbance should be assessed in the context of environmental disaster, while others were of an opinion that a wind disturbance is an excellent opportunity for natural recovery of deciduous and mixed forests. Issues related to protection of the Smreczyńska Polana highland also inspired an interesting debate. Some of the participants believed that natural succession with shrubs is a natural process where no human intervention is needed. On the other hand, others argued that this is one of the very few open areas in which a significant distance from tourist trails produces a safe and quiet place, used especially by large mammals. In addition, maintaining this site as an open area was also proposed due to its landscape value. In spite of the long and interesting discussion, no consensus was achieved in terms of conservation goals in this particular location. During the second day, the participants were divided into four groups, as diverse as possible in terms of participant’s competences, background and expertise. An experienced person representing the TPN staff accompanied each group. The aims of this session included an evaluation of natural resources, assessing the level of habitat alterations, and defining conservation goals and priorities. Participants managed to properly identify most of the issues related to nature conservation, however, conservation goals were the subjects of a long and intensive debate. One of the most significant problems was to decide, which should take a higher priority: natural processes, or active protection of species and habitats. All the participants agreed on the need for regeneration of the part of the valley, which had been heavily altered due to mining and metallurgy. However, differences of opinion occurred during the assessment of environmental effects of the TPN activities. Main concerns were related to the process of forest stand conversion, and planting of European larch of unknown origin. The consensus has been achieved in that matter, despite the existence of different opinions among the participants. The workshop was summarized by the presentations given by each group with a solid justification for presented ideas related to nature protection in the Tatra National Park.
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Ściśle, czynnie czy krajobrazowo? Niedźwiedziom nie jest wszystko jedno (Strict, active or landscape protection? Bears really do care)
Chapter
Full-text available
  • Oct 2018
In the Tatra National Park (TPN), GPS collars are used since 2006. The first collar of that type was deployed on female brown bear, considered to be a problem bear, because she was often looking for food near mountain hotels and cabins. Since then 13 bears, five females and eight males, have been equipped with GPS transmitters, and more than 80 thousand locations of monitored bears have been collected. Only half of these locations are from the TPN territory – out of these 68.1% of the locations were in the strictly protected area (which constitutes 59.5% of the park’s total area); 30.6% were in the actively protected area (27.4% of the park’s area); and 1.3% were in the landscape protection zone (13.1% of the park’s area). Ivlev’s electivity index used to evaluate bears’ electivity toward protective regime showed that strictly protected area is preferred, while landscape protection zone is being avoided.
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Optimal foraging in brown bears: the biogeographical and local approach
Conference Paper
Full-text available
  • Jul 2011
We reviewed 28 studies on brown bear Ursus arctos diet to examine the dietary patterns of the species across its range in relation to geographical and environmental factors. At local scale, we investigated the seasonal variation in bear diet in the eastern Polish Carpathians at individual and population level based on the analysis of ca 1000 scats. We distinguished six main food categories: green vegetation, fleshy fruits, hard mast, supplemental food, insects and vertebrates. We also investigated the activities of radio-collared bears (n=4) by immediate field-inspection of GPS telemetry locations. Among bear activities, we distinguished resting, walking and foraging on six food categories. We related the seasonal share of food categories in bear diet to the amount of time bears devoted to different activities. At a biogeographical level, temperature and snow conditions were the most important factors determining the composition of brown bear diet. Populations in locations with deeper snow cover, lower temperatures and lower productivity consumed more vertebrates and less invertebrates and mast. Environmental conditions, especially climatic factors, shape the nutritional and energetic requirements of bears as well as the local availability of food. In the study area, activity and diet patterns of brown bears changed seasonally. In the spring, bears concentrated their foraging activity on ungulates and supplemental food, which constituted the staple part of the consumed biomass. In summer and early autumn, the diet of bears consisted almost exclusively of fleshy fruits, though they devoted less than 50% of time to feeding on them. The share of hard mast in autumn diet was relatively low when compared to the amount of time spent feeding on them. The percentage of insects in the consumed biomass was also lower than expected from the amount of time devoted to foraging on them in all the seasons.
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