Mk chian, Alexande ; Muelle , Daniel
A icle — Published Ve sion
Clima ic de e minan s o he Ca pa hian eeline and i s
p ojec ed upwa d shi s in esponse o clima e change
Clima ic Change
P o ided in Coope a ion wi h:
Leibniz Ins i u e o Ag icul u al De elopmen in T ansi ion Economies (IAMO), Halle (Saale)
Sugges ed Ci a ion: Mk chian, Alexande ; Muelle , Daniel (2025) : Clima ic de e minan s o he
Ca pa hian eeline and i s p ojec ed upwa d shi s in esponse o clima e change, Clima ic Change,
ISSN 1573-1480, Sp inge Na u e, Be lin, Vol. 178, Iss. 6, pp. 1-23,
h ps://doi.o g/10.1007/s10584-025-03947-y ,
h ps://link.sp inge .com/a icle/10.1007/s10584-025-03947-y
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Recei ed: 29 May 2024 / Accep ed: 2 May 2025
© The Au ho (s) 2025
Alexande Mk chian
[email p o ec ed]
Daniel Muelle
[email p o ec ed]
1 Leibniz Ins i u e o Ag icul u al De elopmen in T ansi ion Economies (IAMO), Theodo -
Liese -S . 2, 06120 Halle (Saale), Ge many
2 Humbold -Uni e si ä zu Be lin, Un e den Linden 6, 10099 Be lin, Ge many
Clima ic de e minan s o he Ca pa hian eeline and i s
p ojec ed upwa d shi s in esponse o clima e change
Alexande Mk chian1· DanielMuelle 1,2
Clima ic Change (2025) 178:109
h ps://doi.o g/10.1007/s10584-025-03947-y
Abs ac
T eelines ep esen a signi ican ecological bounda y in moun ainous egions. Changes
in empe a u e and p ecipi a ion egimes due o clima e change a ec he loca ion o
eelines, con ingen on ine-scale a ia ions in o og aphic and clima ic condi ions. Us-
ing high- esolu ion sa elli e image y, we iden i y he clima ic eeline — he po en ial
uppe limi o o es s de e mined by clima ic condi ions — in he Ca pa hian Moun ains,
one o Eu ope’s la ges con iguous o es ecosys ems. We downscale clima e a iables
o a 30-m esolu ion by applying a polynomial app oxima ion o he eg ession esidu-
als, inco po a ing e ain a ibu es. We hen co ela e clima ic a iables wi h he loca ion
o he clima ic eeline. The mean empe a u e o he wa mes qua e demons a es he
s onges co ela ion wi h eeline loca ion. We ind a o al a ea o 1,370 km2 abo e he
cu en clima ic eeline in he Ca pa hians, which cons i u es he clima ic en elope o
alpine ecosys ems. Depending on u u e clima e p ojec ions, his a ea will dec ease o
410–515 km2 by 2040, 100–320 km2 by 2060, and 15–290 km2 by 2080. The an icipa ed
upwa d shi o he eeline jeopa dizes he egion's a e and endemic alpine species and
has subs an ial ami ica ions o ecosys ems, wa e balance, and he ca bon cycle in he
Ca pa hian Moun ains. Ou analysis highligh s he impo ance o unde s anding how cli-
ma e a ec s eeline loca ions o e ec i e ecosys em managemen and conse a ion plan-
ning in a changing clima e.
Keywo ds Ca pa hian moun ains · Fo es eco one · Moun ain ecosys ems · Ecosys em
shi · Global wa ming · Clima e impac s
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Clima ic Change (2025) 178:109
1 In oduc ion
T ees disappea abo e a speci ic ele a ion, gi ing way o alpine meadows o alpine un-
d a, which ha e subs an ially lowe abo eg ound biomass (Hol meie 2009; Hansson e al.
2023). The line whe e ees disappea , he eeline, connec s he highes pa ches o closed
o es (Paulsen e al. 2000; Kö ne 2004; Czajka e al. 2015b). Typically, hei loca ion is
de e mined by some h eshold o ee heigh and canopy co e (Kö ne 1998; Wiese and
Tausz 2007; Hol meie 2009; T eml and Migoń 2015).
The posi ion o he eelines di e s egionally and locally due o clima ic and edaphic
ac o s, local dis u bance egimes, and an h opogenic land co e changes. Clima ic eeline
e e s o he ansi ions de e mined by clima ic condi ions (Kö ne 2003; Hol meie 2009).
Clima ic eelines exhibi consis en cha ac e is ics ac oss a ious con inen s and la i udes,
se ing as c ucial ecological di ides and c i ical e e ence poin s o moun ain li e zones
(T anquillini 1979; Kö ne and Paulsen 2004; Kö ne e al. 2011). While empe a u e is
widely acknowledged as he c i ical en i onmen al de e minan o he ansi ion om o -
es s o alpine sh ubland and g assland, he p ecise clima ic ac o s and physiological mecha-
nisms go e ning eeline posi ion emain unclea (Paulsen e al. 2000; Hol meie and B oll
2007; Wiese and Tausz 2007; Smi h e al. 2009). Fac o s such as p ecipi a ion and wind
exposu e, which in luence he du a ion o snow co e , along wi h a mosphe ic CO₂ le els
and soil nu ien s a us, also a ec eeline dynamics; howe e , hei impac is ei he less
signi ican o locally speci ic.
T adi ionally, alpine eelines ha e been associa ed wi h a mean ai empe a u e o
app oxima ely 10°C du ing he wa mes mon h in empe a e moun ains (G ace 2002; Wie-
se and Tausz 2007; Richa dson and F iedland 2009; Kö ne 2021). This alue is subs an-
ially lowe in opical egions, whe e he g owing season ex ends almos h oughou he
yea (Kö ne and Paulsen 2004). T eelines a e also associa ed wi h he du a ion o he g ow-
ing season (Ellenbe g and Leuschne 2010) and maximum daily empe a u es in summe
(Daubenmi e 1954). Kö ne (Kö ne 1998, 2021) con ends ha he mean empe a u e o he
g owing season holds global signi icance in de e mining he eeline posi ion. He a ibu es
his o a physiological mechanism ha inhibi s apical me is em ac i i y in esponse o low
empe a u es, impeding ee issue o ma ion. He de ines he g owing season o ees as he
pa o he yea wi h a e age daily empe a u es abo e 0.9⁰C (Kö ne e al. 2011).
I can be assumed ha no single o e a ching biological mechanism o quan i a i e
pa ame e shapes global eeline posi ions. Ins ead, he di e si y o egional and local cli-
ma es, lo al composi ions, and he complexi y o unc ional ela ionships esul in dis inc
a ia ions o al i udinal pa e ns o eelines (Smi h e al. 2009). Fo sepa a e egions wi h
uni o m ecological and opog aphical cha ac e is ics, he assump ion ha a single mecha-
nism go e ns eeline loca ion becomes mo e easonable. Howe e , he p ecise mechanisms
and ela ed clima ic pa ame e s de e mining egional clima ic eeline loca ions emain an
open ques ion o mos moun ain ecosys ems.
Clima e change, p ima ily h ough inc eased empe a u es, p omp s upwa d shi s in
eelines, wi h signi ican implica ions o biodi e si y, endemic alpine species, wa e bal-
ance, nu ien cycling, and ca bon s o age (G eenwood and Jump 2014; Hansson e al.
2021). Bo h clima e change and associa ed eeline shi s a ec o es y managemen and
land use sys ems, such as alpine pas u es (Cannone e al. 2007). While ample e idence
exis s ega ding clima ically induced eeline ascen since he la e wen ie h cen u y (Hol -
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Clima ic Change (2025) 178:109
meie 2009), hese changes mani es slowly due o ees' delayed esponse o changing cli-
ma e. The e o e, mos cu en ly epo ed eeline changes esul ed mainly om changes in
land use p ac ices, including declining anshumance and logging (Geh ig‐Fasel e al. 2007;
Weisbe g e al. 2013). The pa chy unde s anding o clima e change impac s on eeline al e -
a ions is un o una e amids accele a ing clima e change and associa ed ex eme wea he
e en s, which u he inc ease p essu e on moun ain ecosys ems, po en ially ein o cing
upwa d shi s in eeline loca ions.
We in es iga e he ac o s in luencing clima ic eeline posi ion and po en ial shi s in he
eeline loca ions o he Ca pa hian Moun ains, which span se e al coun ies in he cen e
o Eu ope. The Ca pa hians con ain many ecosys ems and clima ic zones, and a e a ho spo
o Eu opean biodi e si y, hos ing nume ous a e and endemic species (M áz and Ronikie
2016). Wi h peak ele a ion eaching only up o 2,655 m, e en modes upwa d ad ancemen s
in he eeline could elimina e alpine habi a s ac oss many o hei moun ain anges. While
ecen ends in he Ca pa hian eeline ha e been assessed wi h sa elli e da a (Mihai e al.
2007; Ma azino a e al. 2011; Weisbe g e al. 2013), he e is cu en ly a lack o quan i i-
ca ion ega ding he in luence o his o ical clima e and expec ed u u e clima e change on
eeline loca ion in he Ca pa hians.
Ou p ima y objec i e in his pape is o iden i y he clima ic ac o s ha de e mine
he loca ion o he cu en clima ic eeline in he Ca pa hians and o p ojec he po en ial
impac s o clima e change on u u e eeline shi s. To accomplish his, we delinea ed he
ex an cu en clima ic eeline agmen s on high- esolu ion emo e sensing image y. We
downscaled he bes a ailable clima ic da a o assess he ine-scale a ia ions in he de e -
minan s o he eeline loca ion. Quan i ying he clima ic a iables inside and ou side hese
agmen s e ealed he a iables wi h he s onges co ela ion wi h he eeline loca ion. We
hen p edic ed he po en ial clima ic eeline loca ions in he en i e Ca pa hian ange and he
app op ia e a eas o clima ic en elopes o alpine ecosys ems based on he h eshold alue
o he mos pe inen clima ic a iable. Finally, we used da a om clima e change scena ios
o p ojec eeline shi s o 2040, 2060, and 2080, conside ing di e en Sha ed Socioeco-
nomic Pa hways (SSPs) (Cope nicus Clima e Change Se ice 2021).
2 Ma e ials and me hods
2.1 S udy a ea
The Ca pa hian Moun ains a e he eas e nmos o shoo o he Cen al Eu opean highlands,
s e ching 1,500 km om Eas o Wes o e six coun ies and co e ing 190,000 km2 (Fig. 1).
Mos o his egion is below he eeline, excep o he highes moun ain anges. These
anges a e app oxima ely e enly dis ibu ed be ween h ee main subdi isions o he Ca -
pa hian Moun ains: he (No h-)Wes e n, Eas e n, and Sou he n Ca pa hians (e.g., Kond-
acki 1989). We inspec ed he highes pa s o he Ca pa hians (abo e 1,300 m) o he
loca ion o eeline. A he same ime, we used he en i e Ca pa hian egion along wi h
adjacen a eas, co e ing a o al o 480,000 km2, o downscaling clima ic a iables.
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Clima ic Change (2025) 178:109
2.2 T eeline delinea ion
We de ine he eeline eco one as he bel a he uppe ele a ional limi o a closed-can-
opy o es , wi h a g adual ege a ion ansi ion om closed ee s ands o open g asslands
and sh ubs. Di use eelines a e mo e o en limi ed by clima ic ac o s, unlike ab up and
k ummholz eelines, which a e mo e likely o be shaped by an h opogenic and na u al dis-
u bances (Ha sch e al. 2009; Hansson e al. 2021; see Fig. {5}). I is indi ec ly con i med
by g adual di use eelines being mo e esponsi e o clima e wa ming (Tou ille e al.
2023).
We manually delinea ed eeline eco ones on high- esolu ion Bing ae ial o hog aphic
images (Mic oso n.d.) wi h 15–30 cm spa ial esolu ion and a spa ial accu acy o a ound
2 m. To do so, we digi ized ee s ands on he espec i e ele a ions wi h isible and apid
bu g adual ele a ional de e io a ion o ee s a u e. We aimed a iden i ying he ypical
ins ances o na u al clima ic eeline h oughou he Ca pa hian Moun ains, digi izing ee
s ands abo e 1300 m a.s.l. ha had cha ac e is ic ele a ional de e io a ion o ee s a u e
(see Fig. {6}, Appendix).
We iden i ied 161 pa ches o clima ic eeline in he highes moun ain anges o he Ca -
pa hians, oge he encompassing an a ea o nea ly 12 km2. Ou sample does no ep esen an
exhaus i e in en o y o he emnan s o he ex an clima ic eeline and may include some
e oneous designa ions, which did no subs an ially in luence ou esul s. The dis ibu ion o
he pa ches e eals h ee dis inc clus e s, each co esponding o a majo subdi ision o he
Ca pa hian Moun ains (Fig. 1). Delinea ed eeline pa ches a e dis ibu ed almos uni o mly
in he highes moun ain anges o he h ee subdi isions. Subs an ial dispa i ies in eeline
ele a ion we e obse ed among he subdi isions, p ima ily along a no h–sou h g adien ,
indica ing ha he cha ac e is ic ele a ion o eeline pa ches changes wi h changing cli-
ma ic condi ions (Table {3}).
Fig.1 S udy a ea
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Clima ic Change (2025) 178:109
2.3 Clima ic a iables and hei spa ial downscaling
We u ilized mon hly clima e da a om 1970 o 2000 a 1 km2 esolu ion om Wo ldClim
2.1 (Fick and Hijmans 2017). We de i ed 12 clima ic a iables o se e as de e minan s o
eeline loca ion. Using clima ic alues o he end o he las cen u y is jus i ied by he lag
o se e al decades in ees' esponse o changing clima e. We selec ed a iables ha cap u e
a ious aspec s o he he mal egime, namely he annual mean empe a u e, mean empe a-
u e o he wa mes qua e o he yea , mean empe a u e o he wa mes mon h (July), max-
imal empe a u e o he wa mes mon h, and minimal empe a u e o he coldes mon h ( he
la e wo a iables e lec he mal and cold s ess, espec i ely). Mos o hese a iables
indica e he mal esou ces a ailable o plan s du ing he mos ac i e g ow h phases, and all
co ela e wi h he al i ude o eelines (G ace 2002; Kö ne and Paulsen 2004). We u he
inco po a ed he mean Oc obe empe a u e, which has been demons a ed o signi ican ly
p edic eeline mo emen in he No he n Hemisphe e (Hansson e al. 2023).
We included g owing season du a ion, g owing season mean empe a u e, and accumu-
la ed g owing deg ee days (AGDD). The la e is he cumula i e sum o daily empe a u es
h oughou he g owing season ha su pass a p ede ined h eshold (Hansson e al. 2021).
We used wo h eshold op ions: 0.9 °C, which de ines he g owing season in high-al i ude
eeline s udies (Kö ne and Paulsen 2004; Paulsen and Kö ne 2014), and 5 °C, which
cap u es he g owing season de ini ion o ees (Kö ne 2003). To accomplish his, we em-
po ally downscaled he ime se ies o mon hly mean empe a u es o daily ime se ies wi h
a cubic smoo hing spline and calcula ed he du a ion o he g owing seasons as he days
when he empe a u e exceeded he h esholds, he mean empe a u e du ing he g owing
seasons, and he AGDD. We used ele a ion in me e s abo e sea le el (m a.s.l.) as ano he
explana o y a iable o e i y i empe a u e- ela ed a iables we e be e p edic o s han
di e ences in ele a ion alone.
Wo ldClim da a ha e al eady been used in he global analysis o eeline ac o s and
dis ibu ions, bu he 1 km esolu ion comp omises he accu acy o he analysis (Kö ne e
al. 2011; Haesen e al. 2023). We hus spa ially downscaled he clima e da a o a esolu ion
o 30 m wi h a spa ial a iabili y model. This model accoun s o local e ain e ec s, such
as empe a u e changes wi h ele a ion and po en ial in luences o e ain aspec . I also
add esses la ge-scale spa ial a iabili y, including empe a u e changes in he no h–sou h
di ec ion and he impac o con inen ali y. Ou downscaling app oach o he 12 clima ic
a iables in ol ed he ollowing s eps:
1) Reg ession models link he clima ic a iables o ele a ion and i s wo de i a i e com-
ponen s in he X and Y di ec ions, which accoun o e ain aspec in luences. Ele a ion
da a was sou ced om he Shu le Rada Topog aphy Mission (SRTM) digi al ele a ion
model ( e sion 3), a ailable in 1-a csecond (~ 30 m) esolu ion (NASA 2014). We used
Akaike and Bayesian in o ma ion c i e ia o decide whe he o include e ain aspec s
in each a iable's model.
2) The eg ession models p edic he a iables a a 30-m esolu ion. We hen calcula ed he
di e ences ( esiduals) be ween hese p edic ions and he o iginal 1-km esolu ion al-
ues o he a iables. These esiduals a e likely due o he emaining la ge-scale spa ial
a iabili y no accoun ed o by e ain a ibu es.
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Clima ic Change (2025) 178:109
3) The esiduals we e smoo hed using o hogonal polynomials in he o m o a 6 h-o de
end su ace. We hen added he eme ging la ge-scale pa e ns o he eg ession mod-
els' p edic ions. The inal p edic ion, he e o e, combines he ine de ails con ingen on
local e ain condi ions wi h he b oade pa e ns associa ed wi h la i ude and la ge-
scale geog aphical ea u es.
We e alua ed he downscaling accu acy wi h wea he s a ion da a om he Global His-
o ical Clima ology Ne wo k (GHCN) da ase (Pe e son and Vose 1997). Wi hin he s udy
egion, we iden i ied 28 wea he s a ions wi h a minimum o 67% alid mon hly eco ds
om 1970 o 1984 and om 1985 o 1999 (Fig. 1). We compu ed he espec i e clima ic
a iables o hese s a ions and de e mined he disc epancies be ween he obse ed wea he
s a ion eco ds, ou downscaled da a, and he o iginal 1 km Wo ldClim da a. This com-
pa ison enabled o examine how much ou downscaled da a enhanced he o iginal 1 km
Wo ldClim da ase .
2.4 Ve i ying ela ions be ween clima ic a iables and eeline loca ion
We i s calcula ed he pai wise co ela ion caoe icien s o all he explana o y a iables o
de e mine he deg ee o uni o mi y and de ec possible edundancy. We hen supe imposed
he downscaled clima ic a iables on he delinea ed eeline pa ches o assess hei co e-
spondence. We employed wo app oaches o he pu pose. The i s explo a i e app oach
assumes ha a iables wi h a s onge associa ion wi h he eeline exhibi g ea e homo-
genei y wi hin he eeline eco one compa ed o he su oundings. To quan i a i ely assess
his co espondence, we calcula ed he a ios o he s anda d de ia ions and coe icien s o
a ia ion o he clima ic a iables wi hin all digi ized eeline pa ches o hei espec i e
backg ound alues. The backg ound s anda d de ia ions and coe icien s o a ia ion we e
de i ed om he ele a ion bel be ween 1,300 and 1,900 m a.s.l. ou side he pa ch bounda -
ies. The smalle hese a ios o a clima ic a iable, he s onge he co espondence be ween
his a iable and he eeline loca ion.
The second app oach in ol ed applying wo machine lea ning models o ela e he
eeline wi h clima ic a iables sampled o e mo e han 7 million pixels in he 1,300–1,900
m a.s.l. ele a ion bel , 18,450 o which we e loca ed inside he eeline pa ches. We used
Random Fo es (RF) and G adien Boos ing Machine (GBM) models om he R Ca e
package and au oma ically ine- uned model pa ame e s o selec he “op imal” model
(Kuhn 2008). Fi s , we calcula ed s a is ics o RF a iable impo ance o each clima ic
a iable (Genue e al. 2010) using 20 samples o 2000 da a poin s – 1000 om a eas inside
and ano he 1000 ou side he eeline pa ches. We epea ed his p ocedu e 20 imes o com-
pu e means and s anda d de ia ions o he a iable impo ance on each o hese 20 samples
(400 model uns in o al). We hen calcula ed s a is ics o he accu acy measu es o RF and
GBM models ha included di e en explana o y a iables and hei combina ions, using 50
eplica ed samples o he 2000 da a poin s. Ou aim was o iden i y he a iables and hei
possible combina ions ha a e mos closely associa ed wi h eeline loca ion. I one single
explana o y a iable p o es su icien o he pu pose, he p esen -day clima ic eeline can
be de ined by i s h eshold alue. In addi ion, i allows iden i ying a eas whe e dis u bances
caused he eeline o descend and de ining he ex en o he clima ic en elope o alpine
ecosys ems abo e he eeline.
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Clima ic Change (2025) 178:109
We hen applied a sepa a e p ocedu e o es ima e he loca ional accu acy o eeline
delinea ions based on clima ic h esholds. Speci ically, we calcula ed he dis ances be ween
he cen oids o ou eeline pa ches and he nea es es ima ed clima ic eeline. Dis ances
we e assigned posi i e alues o cen oids loca ed below he clima ic eeline and nega-
i e alues o hose abo e i . We summa ized hese dis ances using wo me ics: he mean
dis ance ( o cap u e di ec ional bias) and he mean squa ed dis ance ( o quan i y o e all
de ia ion). Each me ic was compu ed in wo ways – i s , ea ing all cen oids equally, and
second, applying weigh s p opo ional o he espec i e pa ch a ea, gi ing he cen oids o
la ge pa ches g ea e in luence.
We also o ecas ed u u e clima ic eeline shi s using clima e p ojec ions. We used
CMIP6 downscaled p ojec ions o ou scena ios o he Sha ed Socioeconomic Pa hways
(SSPs) SSP1-2.6, SSP2-4.5, SPP3-7.0 and SSP5-8.5, each a e aged o e 20-yea pe iods
(2021–2040, 2041–2060, 2061–2080, 2081–2100); he scena io da a a e a ailable h ough
Wo ldClim (O’Neill e al. 2016; Fick and Hijmans 2017; Riahi e al. 2017). A e ages and
s anda d de ia ions we e calcula ed o 23 global clima e models (GCMs) o each SSP and
pe iod. We calcula ed he o al a ea whe e he alue o he indica i e clima ic a iable is
below he es ablished h eshold o he a e age o he models o es ima e he ex en o he
u u e eeline ascen and he co esponding educ ion in he clima ic en elope o alpine
ecosys ems.
3 Resul s
3.1 Downscaling clima ic a iables
The downscaling o clima ic a iables o a 30 m esolu ion subs an ially enhanced hei
spa ial accu acy, as e idenced by compa ing wea he s a ion da a and o iginal Wo ldClim
da a (Table 1). The ex en o accu acy imp o emen di e ed among he a iables: Minimal
empe a u e showed only a modes gain, as an icipa ed, due o commonly occu ing in e ed
e ical empe a u e g adien s a nigh . The accu acy gain exceeded 20% o 8 ou o 12
a iables, a i ming he e ec i eness o he employed downscaling me hod. Consequen ly,
we used he downscaled clima ic laye s in he subsequen analyses (see Fig. {7} o an illus-
a ion o he downscaling e ec ).
3.2 Rela ions be ween clima ic a iables and eeline loca ion
The alues o pai wise co ela ion coe icien s be ween he clima ic a iables sugges a
high deg ee o collinea i y (Fig. {8}). This is especially ue o a iables associa ed wi h
wa m-season empe a u es (Tqua , TJul, Tmax, GP5sum, GP0.9sum), which exhibi co -
ela ion coe icien s o 0.99 o highe among hemsel es. The Tmin a iable, cha ac e izing
he minimal empe a u e o he coldes mon h, is he leas co ela ed wi h o he a iables.
S anda d de ia ions and coe icien s o a ia ion o mos clima ic a iables we e signi i-
can ly smalle wi hin eeline pa ches han in he backg ound ele a ion bel (Fig. 2; Table
{4}). Only o annual mean empe a u e and ele a ion a.s.l. we e hey oughly equal, wi h
a a io close o 1. This indica es ha mos clima ic a iables a e conside ably be e p edic-
o s o he clima ic eeline loca ions han ele a ion alone. Va iables cha ac e izing em-
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Page 7 o 23 109
Clima ic Change (2025) 178:109
pe a u es du ing he wa me pa o he yea exhibi he smalles s anda d de ia ion and
coe icien o a ia ion a ios. Con e sely, minimal and annual mean empe a u es had a
signi ican ly poo e ma ch wi h he eeline loca ion.
The mean empe a u e o he wa mes qua e (Tqua ) a iable exhibi ed signi ican ly
highe impo ance han o he a iables in he Random Fo es models (Fig. 2; Table {5}).
I also demons a ed he la ges di e ence in he coe icien o a ia ion be ween eeline
pa ches and hei backg ound (Fig. 2; Table {4}). Calcula ed s a is ics o he accu acy mea-
su es o RF and GBM models ha conside di e en explana o y a iables and hei com-
bina ions show ha adding o he a iables didn’ imp o e he accu acy o GBM models
and only ma ginally imp o ed he accu acy o RF models (Table 2). The eason is he high
mul icollinea i y o explana o y a iables, pa icula ly hose ela ed o wa m season em-
pe a u es. We he e o e ound i app op ia e o use he Tqua a iable o indica e cu en
and u u e clima ic eeline loca ions.
The h eshold alue o clima ic eeline was de e mined by a e aging he Tqua (mean
empe a u e o he wa mes qua e ) a iable ac oss all eeline pa ches, esul ing in a alue
o 9.96⁰C (see column 2 o Table {4} o he h eshold alues o o he a iables). Based on
his pa ame e , we es ima e he o al a ea o he clima ic en elope o alpine ecosys ems
o be 1,370 km2 (conside ing he mean 1970 o 2000 clima e and he cu en ecosys em
dis ibu ion).
The eeline de ined by he Tqua a iable h eshold aligns well wi h he obse ed
eeline pa ches. O he 161 delinea ed eeline pa ches, 81 a e in e sec ed by he de ined
h eshold line, wi h 36 loca ed abo e i and 44 below. The mean dis ance om pa ch cen-
Table1 Downscaling summa y
Clima ic
a iable
Reg ession model Roo mean squa ed de ia ion om
wea he s a ion da a
Accu-
acy gain o
downscaled
da a, %
Va iables in he
model, sign
Mul iple
R-squa ed
O iginal Wo ldClim
da a
Down-
scaled
da a
Tann Ele , AspX, AspY 0.75 0.78 0.73 5.92
Tqua Ele , AspY 0.82 0.61 0.48 21.5
TJul Ele , AspY 0.83 0.71 0.52 26.2
TOc Ele , AspX 0.72 0.54 0.42 20.3
Tmax Ele 0.80 1.04 0.72 30.4
Tmin Ele , AspY 0.51 1.42 1.40 1.40
GP0.9leng Ele 0.60 283.4 204.8 27.7
GP0.9mean Ele , AspY 0.85 0.26 0.21 18.1
GP0.9sum Ele 0.76 31.8 25.7 19.3
GP5leng Ele 0.47 320.9 159.4 50.3
GP5mean Ele , AspX 0.74 0.72 0.31 56.2
GP5sum Ele 0.74 37.0 28.45 23.1
Clima ic a iables: Tann Annual mean empe a u e; Tqua Mean empe a u e o he wa mes qua e ;
TJul Mean July empe a u e; TOc Mean Oc obe empe a u e; Tmax Mean maximal empe a u e o he
wa mes mon h; Tmin Mean minimal empe a u e o he coldes mon h; GP0.9leng Du a ion o he g owing
season abo e 0.9 °C; GP0.9mean Mean empe a u e o he g owing season abo e 0.9 °C; GP0.9sum AGDD
o he g owing season abo e 0.9 °C; GP5leng Du a ion o he g owing season abo e 5 °C; GP5mean
Mean empe a u e o he g owing season abo e 5 °C; GP5sum AGDD o he g owing season abo e 5 °C.
Explana o y e ain a ibu es (Column 2): Ele – Ele a ion (m a.s.l.); AspX – ele a ion de i a i e in X
di ec ion (no h–sou h); AspY – ele a ion de i a i e in Y di ec ion (eas –wes )
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109 Page 8 o 23
Clima ic Change (2025) 178:109
2005; Reyes-Fox e al. 2014), which could ampli y and e en locally ou weigh he e ec s o
p edic ed empe a u e inc eases (Higgins and Schei e 2012).
I ou assump ion ha summe empe a u es a e he leading ac o behind clima ic
eelines is alid, he d as ic dec ease in he clima ic en elope o alpine ecosys ems in he
Ca pa hians should be expec ed by he end o he cen u y. This means ha he e o s o
he conse a ion o alpine communi ies, including hei endemic and endange ed species,
should be spa ially di ec ed owa ds he highes idges and peaks in he Ca pa hians, in pa -
icula he Ta as and Sou he n Ca pa hians, whe e a o able clima ic condi ions o hese
ecosys ems would sus ain o longe . The choice o SSP scena io signi ican ly in luences he
p ojec ions, wi h he di e gence in he es ima ed a eas abo e he clima ic eeline inc easing
p og essi ely o e ime ac oss he ou scena ios (Fig. 4). This means ha global measu es
o slow down clima e wa ming a e essen ial o educing he de imen al e ec s o clima e
change on moun ain ecosys ems.
5 Conclusions
Ou s udy e eals he clima ic ac o s ha go e n he cu en eeline posi ion in he Ca -
pa hians, and p ojec s i s upwa d shi s unde clima e change. Wa m season empe a u es
a e he mos in luen ial o he uppe bounds o ee g ow h and he mean empe a u e o he
wa mes qua e exhibi s he s onges co ela ion wi h eeline loca ion among he 12 cli-
ma ic a iables es ed in ou s udy. We used he es ima ed h eshold alue o he mean em-
pe a u e o he wa mes qua e o assess he cu en o al a ea o he clima ic en elope o
alpine ecosys ems a 1,370 km2. Using CMIP6 clima e p ojec ions, we o ecas he dec ease
o alpine ecosys ems o less han a qua e o hei cu en size by 2050. In he highes emis-
sion scena ios, alpine ecosys ems in he Ca pa hians will almos en i ely disappea by 2080.
Ou wo k co obo a es he impo ance o educing g eenhouse emissions o sa egua d
alpine ecosys ems bu also unde sco es he need o adap a ion measu es o suppo moun-
ain egions. We ill a egional gap in quan i ying eeline beha io unde clima e change.
Un o una ely, such es ima es a e s ill lacking o o he c i ical moun ain sys ems, such as
he neighbo ing Alps and Dina ic moun ains, which sha e compa able clima e and eco-
sys em p ope ies. We hope ou esul s con ibu e o mo e de ailed s udies ha del e in o
physiological mechanisms and en i onmen al in e connec ions o acili a e a deepe unde -
s anding o he ecological consequences o clima e wa ming. Such knowledge is c ucial o
imp o ing land use managemen and adap a ion s a egies o moun ain o es y, ag icul-
u e, and na u e conse a ion amids accele a ing clima e change.
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Clima ic Change (2025) 178:109
Appendix
Fig.6 Two examples o manually iden i ied ins ances o na u al clima ic eeline
Fig.5 Land use mosaics o o es and g assland pa ches shaped by humans ( op ow) and clima ic eeline
eco ones (bo om ow). Na u al eelines ypically g adually ansi ion om o es o g assland along
al i udinal g adien s, whe eas ab up o es edges a e gene ally a sign o human o na u al dis u bances
1 3
109 Page 16 o 23
Clima ic Change (2025) 178:109
Fig.7 F agmen s o ini ial ( op) and downscaled (bo om) laye s o mean July empe a u e
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Clima ic Change (2025) 178:109
Table3 Dis ibu ion and cha ac e is ics o iden i ied eeline pa ches
Ca pa hian
subdi ision
Numbe o
pa ches
To al
a ea,
km2
Mean
pa cel
a ea, ha
Ele a ion,
mean, m
Ele a ion,
median, m
Ele a ion,
s anda d
de ia ion, m
El-
e a ion,
mini-
mal, m
Ele a-
ion,
maxi-
mal, m
No h-Wes 48 3.19 6.65 1,578 1,554 97 1,384 1,858
Eas 69 5.25 7.61 1,684 1,695 90 1,453 1,921
Sou h 44 3.54 8.05 1,848 1,845 42 1,701 1,983
To al 161 11.98 7.44 1,704 1,723 131 1,384 1,983
Fig.8 Pai wise co ela ion coe icien s be ween he clima ic a iables
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109 Page 18 o 23
Clima ic Change (2025) 178:109
Table4 Means, s anda d de ia ions and coe icien s o a ia ion o downscaled clima ic a iables wi hin
eeline pa ches and in he backg ound (1300–1900 m a.s.l. ele a ion bel in Ca pa hians)
Clima ic
a iable
T eeline pa ches In backg ound Ra io o SD Ra io o CV
Mean SD CV Mean SD CV
Tann, °C 1.52 0.62 0.002 2.24 0.68 0.002 0.92 0.93
Tqua , °C 9.96 0.42 0.001 11.17 0.90 0.003 0.47 0.47
Tjul, °C 10.54 0.44 0.002 11.75 0.90 0.003 0.49 0.49
Toc , °C 3.03 0.44 0.002 4.04 0.80 0.003 0.55 0.55
Tmax, °C 15.17 0.52 0.002 16.62 1.08 0.004 0.49 0.49
Tmin, °C -12.5 0.64 0.002 -11.49 0.98 0.004 0.64 0.65
GP0.9leng, days 191.2 6.93 0.036 206.5 12.63 0.061 0.55 0.59
GP0.9mean, °C 7.62 0.24 0.0008 8.21 0.463 0.002 0.51 0.51
GP0.9sum,
AGDD
1243 116.4 0.002 1571 246.1 0.004 0.47 0.51
GP5leng, days 143.9 5.86 0.041 157.5 11.42 0.073 0.51 0.56
GP5mean, °C 9.31 0.30 0.001 10.02 0.54 0.002 0.56 0.56
GP5sum, AGDD 1112 115.8 0.003 1436 247.4 0.006 0.47 0.51
Ele a ion,
m a.s.l
1704 130.5 0.077 1572 131.8 0.094 0.99 0.91
SD s anda d de ia ion (pa ches/backg ound); CV coe icien o a ia ion (pa ches /backg ound)
Clima ic a iables: Tann Annual mean empe a u e; Tqua Mean empe a u e o he wa mes qua e ;
TJul Mean July empe a u e; TOc Mean Oc obe empe a u e; Tmax Mean maximal empe a u e o he
wa mes mon h; Tmin Mean minimal empe a u e o he coldes mon h; GP0.9leng Du a ion o he g owing
season abo e 0.9°C; GP0.9mean Mean empe a u e o he g owing season abo e 0.9°C; GP0.9sum AGDD
o he g owing season abo e 0.9°C; GP5leng Du a ion o he g owing season abo e 5°C; GP5mean Mean
empe a u e o he g owing season abo e 5°C; GP5sum – AGDD o he g owing season abo e 5°C
Va iable Va iable impo ance
Mean S anda d de ia ion
Tann 15.24 9.59
Tqua 99.68 0.4
Tjul 49.09 14.26
Toc 2.23 2.04
Tmax 17.12 9.11
Tmin 14.66 4.19
GP0.9leng 1.04 0.97
GP0.9mean 37.5 12.65
GP0.9sum 3.53 2.25
GP5leng 18.64 8.11
GP5mean 16.54 8.49
GP5sum 22.07 10.13
Table5 Va iables impo ance in
a se o Random o es models
wi h 20 subsamples o 2000 da a
poin s (see ex )
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Page 19 o 23 109
Clima ic Change (2025) 178:109
Acknowledgmen s We wish o acknowledge he anonymous e iewe s o hei hough ul commen s and
cons uc i e sugges ions, which g ea ly imp o ed he quali y and cla i y o his manusc ip .
Au ho con ibu ions Bo h au ho s con ibu ed o he s udy concep ion and design, da a collec ion and analy-
sis, w i ing he i s d a o he manusc ip and i s subsequen edi ing. All au ho s ead and app o ed he inal
manusc ip .
Funding Open Access unding enabled and o ganized by P ojek DEAL.
The au ho s decla e ha no unds, g an s, o o he suppo we e ecei ed du ing he p epa a ion o his
manusc ip .
Da a a ailabili y The esea ch is based on open da a men ioned and ci ed i he manusc ip .
Da ase s c ea ed du ing he esea ch p ocess a e accessible om Zenodo open eposi o y by he ollowing
links:
Es ima ed clima e eeline in Ca pa hians: h ps://zenodo.o g/ eco ds/11359344
P edic ed clima ic eeline loca ion in Ca pa hians: h ps://zenodo.o g/ eco ds/11358952
Ca pa hian eeline samples: h ps://zenodo.o g/ eco ds/11320218
Cen oids o eeline pa ches: h ps://zenodo.o g/ eco ds/15282320
Code a ailabili y Code o es ing he signi icance o clima ic a iables in ML models:
h p s : / / g i h u b . c o m / a l e m k / C l i m a i c _ d a a / b l o b / m a i n / V a i a b l e _ e s i n g . R
In e media e da a and code a e a ailable om he co esponding au ho by eques .
Decla a ions
Con lic o in e es The au ho s ha e no ele an inancial o non- inancial in e es s o disclose.
Open Access This a icle is licensed unde a C ea i e Commons A ibu ion 4.0 In e na ional License,
which pe mi s use, sha ing, adap a ion, dis ibu ion and ep oduc ion in any medium o o ma , as long as
you gi e app op ia e c edi o he o iginal au ho (s) and he sou ce, p o ide a link o he C ea i e Commons
licence, and indica e i changes we e made. The images o o he hi d pa y ma e ial in his a icle a e
included in he a icle’s C ea i e Commons licence, unless indica ed o he wise in a c edi line o he ma e ial.
I ma e ial is no included in he a icle’s C ea i e Commons licence and you in ended use is no pe mi ed
Yea s
SSP
2021–40 2041–60 2061–80
1–2.6 514.42 318.35 288.81
2–4.5 506.15 227.87 110.61
3–7.0 480.01 169.96 40.37
5–8.5 409.93 99.55 14.76
Table7 Es ima ed a eas, km2,
abo e clima ic eeline based
on downscale a e ages o 23
GCMs p ojec ions o he mean
empe a u e o he wa mes
qua e (cu en alue es ima ed
a 1,370 km2)
Va iable Unweigh ed cen oids Weigh ed cen oids
Mean dis ance Roo mean
squa ed
dis ance
Mean
dis ance
Roo
mean
squa ed
dis ance
Tqua 140.78 206.1 144.8 220.4
Tann 113.8 348.7 254.5 380.2
TJul 145.6 210.5 151.9 230.8
Tmax 192.7 440.4 183.7 366.8
GP5summ 147.1 207.0 159.6 232.3
GP0.9mean 140.7 214.9 152.2 243.2
Ele a ion 331.6 1635.6 520 1247.2
Table6 Dis ances be ween
pa ch cen oids and he nea es
eeline, calcula ed by ea ing
all cen oids equally, and by
applying weigh s o cen oids
p opo ional o he a eas o he
espec i e pa ches
1 3
109 Page 20 o 23
Clima ic Change (2025) 178:109
by s a u o y egula ion o exceeds he pe mi ed use, you will need o ob ain pe mission di ec ly om he
copy igh holde . To iew a copy o his licence, isi h p://c ea i ecommons.o g/licenses/by/4.0/.
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