21
The pas , p esen , and u u e dis ibu ion o Calan he g acili lo a:
implica ions o conse a ion and phylogeog aphy
Ping ing Guo1, Aixian Lu2, Jiahao Zheng1, Lunyan Chen3, Shasha Wu1, Chao Hu4, Muyang Li1,
Weichang Huang4, Junwen Zhai1
1 Key Labo a o y o Na ional Fo es y and G assland Adminis a ion o O chid Conse a ion and U iliza ion a College o Landscape A chi ec u e and A ,
Fujian Ag icul u e and Fo es y Uni e si y, Fuzhou 350002, China
2 Guangxi Mode n Poly echnic College, Hechi 547000, China
3 Pinglongshan Fo es Cen e, Guangxi 538021, China
4 Eas e n China Conse a ion Cen e o Wild Endange ed Plan Resou ces, Shanghai Chenshan Bo anical Ga den, Shanghai 201602, China
Co esponding au ho : Weichang Huang ([email p o ec ed]); Junwen Zhai ([email p o ec ed])
Copy igh : © Ping ing Guo e al.
This is an open access a icle dis ibu ed unde
e ms o he C ea i e Commons A ibu ion
License (A ibu ion 4.0 In e na ional – CC BY 4.0).
Resea ch A icle
Abs ac
Calan he g acili lo a, an o chid species endemic o China, is one o he mos widely dis-
ibu ed membe s o he genus Calan he, occupying he highes la i udinal ange and
exhibi ing s ong cold ole ance. These ai s sugges key adap a ions o di e se and
ex eme en i onmen s, making i an ideal model o s udying plan esponses o clima e
a iabili y. Ecological niche models (ENMs) a e powe ul ools o simula ing species’
po en ial dis ibu ions ac oss di e en ime pe iods, he eby aiding biodi e si y conse -
a ion. In his s udy, 75 il e ed occu ence eco ds o C. g acili lo a and 19 clima ic a i-
ables, de i ed om ield su eys and he ba ium eco ds in China, we e used o model
he species’ po en ial dis ibu ion ac oss 6 pe iods (Las In e glacial, Las Glacial Max-
imum, Middle Holocene, Cu en , Fu u e 2050s, and Fu u e 2070s). Resea ch indings
indica e ha key en i onmen al ac o s in luencing i s dis ibu ion include mean diu nal
empe a u e ange (bio2), mean empe a u e o he wa mes qua e (bio10), annual
p ecipi a ion (bio12), and p ecipi a ion o he d ies mon h (bio14). His o ically, sui able
habi a s o C. g acili lo a we e p ima ily concen a ed sou h o he Qinling-Huaihe Ri e
egion, closely associa ed wi h he Qinling, Luoxiao, Nanling, and Moun Wuyi anges.
Du ing he Las Glacial Maximum, ex ensi e sui able habi a s exis ed in sou hwes e n
China, subsequen ly con ac ing o e ugia in he Qinling and Moun Wuyi a eas, unde -
sco ing hese egions as e ugia o C. g acili lo a. Fu u e p ojec ions indica e an o e all
decline in sui able habi a , highligh ing he signi ican impac s o global wa ming on
i s long- e m su i al. No ably, his s udy ep esen s he i s applica ion o he Max-
En model o in e his o ical e ugia o C. g acili lo a while simul aneously in eg a ing
analyses o i s u u e dis ibu ion shi s. This wo k ills he gap in long- e m clima e
esponse esea ch o his species and e alua es he impac s o clima e change on i s
dis ibu ion, p o iding aluable insigh s o i s phylogeog aphy and conse a ion p ac-
ice. By u he iden i ying co e habi a s and cla i ying hei clima e sensi i i y, he ind-
ings p o ide a basis o de eloping a ge ed conse a ion s a egies ha p io i ize key
ecological a eas and mi iga e he isk o habi a loss.
Key wo ds: Clima e change, geog aphical dis ibu ion, MaxEn model
Academic edi o : Muhammad Rais
Recei ed:
23 Ap il 2025
Accep ed:
13 Sep embe 2025
Published:
10 Oc obe 2025
ZooBank: h ps://zoobank.
o g/9D6A40C8-97B9-4D81-B8A1-
A7C6A6236A94
Ci a ion: Guo P, Lu A, Zheng J, Chen
L, Wu S, Hu C, Li M, Huang W, Zhai J
(2025) The pas , p esen , and u u e
dis ibu ion o Calan he g acili lo a:
implica ions o conse a ion and
phylogeog aphy. Na u e Conse a ion
60: 21–38. h ps://doi.o g/10.3897/
na u econse a ion.60.156661
Na u e Conse a ion 60: 21–38 (2025)
DOI: 10.3897/na u econse a ion.60.156661
22
Na u e Conse a ion 60: 21–38 (2025), DOI: 10.3897/na u econse a ion.60.156661
Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
In oduc ion
E idence is moun ing ha he dis ibu ion pa e ns o species a e in luenced
by apid empe a u e changes, including shi s in empe a u e, p ecipi a ion,
and o he clima ic ac o s (Co le and Wes co 2013; Du e al. 2024; Zhu e al.
2024). In pa icula , dec eases in empe a u e ypically cause species o e ea
o lowe la i udes and al i udes, whe eas wa ming p omo es expansion owa d
highe la i udes and al i udes (Spence and Tingley 2020). Du ing he Las Gla-
cial Maximum (LGM), he high-al i ude moun ains o he Qinghai–Tibe Pla eau
ac ed as a ba ie o he eas wa d expansion o high-la i ude glacie s in Asia
(Deng and Ding 2015; Zhou e al. 2017). This allowed many high-al i ude egions
in China, including he Qinghai–Tibe Pla eau, Daba Moun ains, Wushan Moun-
ains, Dalou Moun ains, Wuling Moun ains, Shennongjia Fo es y Dis ic , Nan-
ling Moun ains, Moun Wuyi, and he moun ains o Taiwan, o se e as glacial
e ugia o plan s (Chen e al. 2011). Du ing his pe iod, species ei he mig a ed
o e ugia o e ol ed in si u h ough gene ic a ia ion o cope wi h empe a u e
luc ua ions. Howe e , i mig a ion o adap a ion could no keep up wi h clima e
change, species would ace popula ion decline, ange con ac ion, o ex inc ion
(Webb 1997; Wiens and G aham 2005). Fu he mo e, human ac i i ies ha e ex-
ace ba ed habi a agmen a ion, posing inc easing h ea s o plan di e si y. As
hese impac s in ensi y, unde s anding bo h he his o ical and po en ial u u e
dis ibu ions o endange ed species is c i ical o biodi e si y conse a ion.
Ecological niche models (ENMs) a e powe ul ools o p edic ing species
dis ibu ions based on known occu ence eco ds and en i onmen al a iables.
These p edic ions a e gene a ed h ough algo i hmic modeling and can be p o-
jec ed ac oss di e en empo al and spa ial scales (A aújo and Pe e son 2012).
The model can be applied o simula e he po en ial ange o species unde di -
e en pe iods and clima ic condi ions, which is c ucial o unde s anding how
species espond o di e se clima ic condi ions. Cu en ly, commonly used ENMs
include GARP (Eli h e al. 2006), BIOCLIM (Nix 1986), DOMAIN (Ca pen e e al.
1993), and he MaxEn model (Phillips and Dudík 2008; Eli h e al. 2011; Liu e al.
2021). Among hem, he MaxEn model (i.e., maximum en opy model) is widely
used o p edic ing plan and animal dis ibu ions. I is a o ed o i s as p o-
cessing, high accu acy, and abili y o pe o m well wi h limi ed dis ibu ion da a
compa ed o o he models (Kaky e al. 2020; Liu e al. 2021; Zhang e al. 2021a).
C. g acili lo a, a pe ennial he b, belongs o he genus Calan he in he O chidace-
ae (sub am. Epidend oideae). I is one o he mos widely dis ibu ed species
o he genus Calan he, wi h he b oades la i udinal ange and he g ea es cold
ole ance. I is p ima ily dis ibu ed in sub opical mon ane o es s o China,
mainly in he Qinling Moun ains, Daba Moun ains, Luoxiao Moun ains, Nanling
Moun ains, and Moun Wuyi, all o which all wi hin he sub opical monsoon
zone, whe e p ecipi a ion is abundan ye s ongly seasonal (Clay on and C ibb
2013). These egions a e cha ac e ized by e e g een b oad-lea ed o es s a ele-
a ions o 600–1500 m and mixed coni e ous–b oadlea o es s a 1500–2500
m. The high humidi y (>75%), acidic, humus- ich soils (pH 5.0–6.5), and shaded
unde s o ies p o ide op imal mic ohabi a s o he species (Chen e al. 1999).
The species is belie ed o ha e o igina ed on he Asian con inen and is endem-
ic o China, di e ging om i s ances o in he ea ly Pleis ocene (2.5 Ma) (Chen
2020). Howe e , he changes in i s geog aphical dis ibu ion om he Pleis ocene
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Na u e Conse a ion 60: 21–38 (2025), DOI: 10.3897/na u econse a ion.60.156661
Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
o p ojec ed condi ions in he 2070s, as well as he loca ion o i s po en ial glacial
e ugia in China, emain unclea . Fu he mo e, sympa ic dis ibu ion, o e lapping
lowe ing pe iods, and hyb idiza ion be ween C. g acili lo a and closely ela ed
species play key oles in main aining species di e si y and s abilizing o es eco-
sys ems (Ca pen e e al. 1993). C. g acili lo a is also alued o i s colo ul low-
e s and i s medicinal p ope ies, making i highly sough a e o o namen al and
medicinal use. Ne e heless, human ac i i ies, combined wi h habi a loss and
clima e change, ha e led o signi ican annual declines in i s na u al popula ions.
Ongoing moun ain de elopmen has pa icula ly con ibu ed o habi a loss, caus-
ing localized popula ion ex inc ions in sou heas e n China (Qiu e al. 2023). Cu -
en ly, he species is lis ed as a nea h ea ened (NT) species by he In e na ional
Union o Conse a ion o Na u e (IUCN). I is also included unde he Con en ion
on In e na ional T ade in Endange ed Species o Wild Fauna and Flo a (CITES),
wi h in e na ional ade s ic ly p ohibi ed and egula ed. Al hough C. g acili lo a
has a b oad geog aphic ange, i is highly sensi i e o mic oen i onmen al chang-
es and exhibi s speci ic ecological niche p e e ences, making i a po en ial indi-
ca o species o assessing he impac s o clima e change on mon ane plan s.
The e o e, he MaxEn model was used o p edic he po en ial dis ibu ion a eas
o C. g acili lo a unde 6 pe iods: Las In e glacial (LIG), Las Glacial Maximum
(LGM), Middle Holocene (MH), Cu en , and Fu u e (2050s, 2070s). The s udy ex-
plo ed he ollowing wo ques ions: (1) Wha we e he po en ial e ugia o he spe-
cies du ing he LGM? (2) How ha e he spa ial dis ibu ion pa e ns and sui able
habi a a eas o he species shi ed om he Pleis ocene o p ojec ions o he
2070s? This s udy p o ides a amewo k o unde s anding he phylogeog aphy
and guiding he conse a ion o C. g acili lo a and o he mon ane o chid species.
Ma e ials and me hods
Species dis ibu ion da a collec ion
Occu ence eco ds o C. g acili lo a we e mainly ob ained om he Chinese
Vi ual He ba ium (CVH, h ps://www.c h.ac.cn/, accessed on 20 July 2022),
Global Biodi e si y In o ma ion Facili y (GBIF, h ps://www.gbi .o g/, accessed
on 21 July 2022), and Flo a o China. A o al o 229 la i ude and longi ude e-
co d poin s o he species we e ga he ed om ele an li e a u e and ieldwo k
eco dings. A 1 km × 1 km bu e zone was es ablished ac oss China using
A cGIS 10.8.1 (ESRI 2020). To educe spa ial bias om clus e ed sampling,
edundan and misiden i ied eco ds we e emo ed, and only one occu ence
poin was e ained pe bu e zone o subsequen ecological niche modeling.
En i onmen al a iable da a acquisi ion
Nine een bioclima ic ac o s in six di e en pe iods we e downloaded om
Wo ldClim (h p://www.wo ldclim.o g/), including he Las In e glacial (LIG,
120ka), Las Glacial Maximum (LGM, 22 ka), Middle Holocene (MH, 6 ka), Cu -
en , and Fu u e ( he 2050s, 2070s). The spa ial esolu ion was 30″. Clima e
da a we e ob ained om he CCSM4 model de eloped by he Na ional Cen e
o A mosphe ic Resea ch (NCAR) unde he amewo k o he Coupled Model
In e compa ison P ojec Phase 5 (CMIP5). CCSM4 was chosen o i s well-doc-
24
Na u e Conse a ion 60: 21–38 (2025), DOI: 10.3897/na u econse a ion.60.156661
Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
umen ed pe o mance in simula ing global and egional clima e p ocesses
(Gen e al. 2011) and i s demons a ed u ili y in ecological s udies, such as
p edic ing species–communi y decoupling unde clima e change (Thomas e
al. 2023). The model’s high- esolu ion ou pu s and educed biases in c i ical
a iables ensu ed obus ness o biogeog aphical analyses. Fo u u e p ojec-
ions in he 2050s and 2070s, he Rep esen a i e Concen a ion Pa hway (RCP)
2.6 scena io was used. This low-emission pa hway aligns wi h global clima e
mi iga ion e o s, p o ides a conse a i e es ima e o po en ial clima e im-
pac s on species dis ibu ions, and allows compa abili y wi h ecen s udies
on h ea ened axa unde op imis ic scena ios. Subsequen ly, he Mask ool in
A cGIS 10.8.1 (ESRI 2020) was used o clip and ex ac egional clima e da a in
China and hen con e hem o ASCII o ma o u he analysis.
En i onmen al a iable da a sc eening
Mul icollinea i y among 19 clima ic a iables can lead o model o e i ing,
which a ec s he e alua ion o simula ion esul s (G aham 2003; Zhang e al.
2014). The e o e, en i onmen al ac o s wi h a small con ibu ion a | | ≥ 0.8
we e emo ed using Pea son co ela ion analysis. Se en en i onmen al ac o s
we e inally iden i ied o model p edic ion, including mean diu nal ange (bio2),
iso he mali y (bio3), minimum empe a u e o he coldes mon h (bio6), mean
empe a u e o he we es qua e (bio8), mean empe a u e o he wa mes
qua e (bio10), annual p ecipi a ion (bio12), and p ecipi a ion o he d ies
mon h (bio14). As o chids a e highly sensi i e o wa e a ailabili y and season-
al d ough (Zo z and Bade 2009; Gao e al. 2025), and p ecipi a ion has been
shown o be a majo de e minan o o chid dis ibu ions (Qiu e al. 2023; Pica
e al. 2024; Tsi sis e al. 2024), bio12 and bio14 we e p io i ized unde collin-
ea i y o ep esen o e all wa e supply and d ough s ess in he sub opical
monsoon egions whe e C. g acili lo a occu s.
MaxEn model building and pa ame e se ing
We collec ed en i onmen al da a and species occu ence poin s ac oss six ime
pe iods, ocusing on clima e a iables ha signi ican ly a ec species sui abili-
y. Clima e da a o each pe iod we e ma ched wi h species dis ibu ion poin s.
The en i onmen al da a (*.asc) and dis ibu ion poin s o C. g acili lo a (*.cs )
we e impo ed in o he MaxEn p og am o habi a dis ibu ion modeling. We
andomly selec ed 75% o he da a as he aining se and 25% as he es se o
model e alua ion. To imp o e me hodological igo and add ess po en ial unce -
ain ies in con en ional MaxEn modeling, we complemen ed he co e modeling
p ocess wi h addi ional e alua ions o en i onmen al a iable impo ance and
species–en i onmen esponse cu es. Va iable con ibu ions we e quan i ied
using jackkni e es s, while esponse cu es we e analyzed o e i y he plausibil-
i y o adap i e h esholds o key clima ic ac o s. Toge he , hese supplemen a y
analyses allowed o a mo e obus iden i ica ion o en i onmen al d i e s and
educed biases in model ou pu s. Model se ings included a maximum o 1000
i e a ions o ensu e con e gence, wi h 10 boo s ap eplica es o imp o e s abil-
i y. The andom seed op ion was applied, and he a e age ou pu ac oss epli-
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Na u e Conse a ion 60: 21–38 (2025), DOI: 10.3897/na u econse a ion.60.156661
Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
ca es was used as he inal p edic ion. Model pe o mance was e alua ed using
he a ea unde he ecei e ope a ing cha ac e is ic cu e (AUC), whe e alues o
0.50–0.60 indica e in alid p edic ions, 0.60–0.70 poo , 0.70–0.80 ai , 0.80–0.90
good, and 0.90–1.00 excellen (Phillips e al. 2006; Phillips and Dudík 2008).
Di ision o sui able egions
The MaxEn model esul s we e impo ed in o A cGIS 10.8.1 o u he analy-
sis. Po en ial dis ibu ion maps o di e en ime pe iods we e classi ied in o
sui abili y ca ego ies and hen isualized. Based on he model’s equal aining
sensi i i y and speci ici y h esholds, i ness zones we e ca ego ized in o ou
le els: unsui abili y, low sui abili y, mode a e sui abili y, and high sui abili y. Po-
en ial dis ibu ion a eas wi h di e en sui abili y le els we e ob ained h ough
a ea abula ion using he SDM oolbox in A cGIS 10.8.1 (ESRI 2020).
Resul s
O e iew o e i ied dis ibu ion eco ds
A o al o 75 occu ence eco ds we e e ained a e spa ial il e ing and da a
alida ion and we e used o subsequen ecological niche modeling (Fig. 1).
These occu ence poin s a e b oadly dis ibu ed ac oss he mon ane egions
o cen al, eas e n, and sou he n China, pa icula ly in Sichuan, Hunan, Jiangxi,
Zhejiang, Fujian, Guangdong, and Guangxi p o inces. The alida ed dis ibu ion
eco ds span a wide ange o la i udes and ele a ions in cen al and sou he n
China, wi h no able concen a ions in sub opical moun ainous a eas.
Sc eening o dominan en i onmen al ac o s
The en i onmen al a iables used in he MaxEn model we e selec ed based
on hei ecological ele ance o C. g acili lo a and hei a ailabili y in he Wo ld-
Clim da abase (Man hey and Box 2007; Fick and Hijmans 2017; Sun e al.
2020). Nine een bioclima ic a iables om he Wo ldClim da ase we e ini ially
assessed, and highly collinea p edic o s (| | > 0.8) we e excluded based on
Pea son co ela ion analysis. Ecologically ele an a iables, pa icula ly p e-
cipi a ion- ela ed ac o s, we e p io i ized due o he species’ associa ion wi h
dis inc d y and we seasons. The esul s o he e ec s o en i onmen al ac-
o s on species dis ibu ion in he MaxEn model showed ha he la ges con i-
bu ion a e was he p ecipi a ion o he d ies mon h (bio14). This was ollowed
by bio12, bio10, and bio2 (Table 1). The cumula i e con ibu ion o hese ou
ac o s accoun ed o 92%. These indings indica e ha he dis ibu ion o C.
g acili lo a is s ongly in luenced by hese en i onmen al condi ions.
The esul s o he a iable-impo ance jackkni e es showed ela i ely high
gain alues o bio2 and bio12 when only a iables we e used (Fig. 2). This indi-
ca ed ha hese en i onmen al ac o s con ibu ed mo e s ongly o he dis i-
bu ion o C. g acili lo a. When a single a iable was igno ed, bio10 showed he
g ea es d op in model gain, implying ha his a iable con ained in o ma ion
ha o he a iables did no .
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Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
Figu e 1. Geospa ial dis ibu ion o e ec i e occu ence eco ds o C. g acili lo a. No e: The colo o each e ec i e poin
indica es he p o ince whe e i is loca ed, and he pu ple lines indica e majo moun ains mapped using he Digi al Moun-
ain Map o China (Nan e al. 2022).
Figu e 2. Impac o bioclima ic a iables on he p edic i e pe o mance o C. g acili lo a dis ibu ion.
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Na u e Conse a ion 60: 21–38 (2025), DOI: 10.3897/na u econse a ion.60.156661
Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
In summa y, he en i onmen al ac o s ha ing signi ican e ec s on he geo-
g aphic dis ibu ion o C. g acili lo a we e bio2, bio10, bio12, and bio14. These
a iables we e selec ed because hey ep esen c i ical clima ic h esholds
o plan su i al and g ow h, pa icula ly in sub opical and mon ane egions
whe e C. g acili lo a is p edominan ly ound.
The esponse cu e esul s o he ou main clima e ac o s a e shown in
Fig. 3. When he p esence p obabili y was g ea e han 0.5, he ange o e-
sponse alues o he mean diu nal ange was 6.3–8 °C, he ange o he mean
empe a u e o he wa mes qua e was 21.5–25 °C, he ange o he annual
p ecipi a ion was 1,500–2,800 mm, and he ange o he p ecipi a ion o he
d ies mon h was 30–170 mm. These anges align wi h he known ecological
p e e ences o C. g acili lo a, u he alida ing he selec ion o hese a iables.
MaxEn model accu acy es ing
The a e age AUC o he p edic ion model o he habi a sui abili y o C. g acili-
lo a unde cu en clima e condi ions was 0.989, wi h a s anda d de ia ion o
0.001. This alue ma kedly exceeded he simula ed andom p edic ion dis ibu-
ion alue o 0.5, demons a ing high accu acy and eliabili y o he p edic ion
esul s (Fig. 4).
P edic ion o sui able egions
As shown in Fig. 5, he sui able egions o C. g acili lo a in six di e en pe i-
ods we e p ima ily dis ibu ed in he sub opical e e g een b oad-lea ed o -
es s sou h o he Qinling–Huaihe line and we e closely ela ed o he Hengduan
Moun ains, Qinling Moun ains, Luoxiao Moun ains, Nanling Moun ains, Moun
Wuyi, and Taiwan Moun ains. The highly sui able egions we e s ably dis ibu ed
in Moun Wuyi and he Luoxiao Moun ains. The mode a ely and poo ly sui able
egions we e mainly concen a ed in he Qinling Moun ains, Nanling Moun ains,
and Taiwan Moun ains, as well as su ounding he highly sui able egions.
P edic ion o sui able egions in he pas pe iod
Du ing he LIG (Fig. 5a), he sui able habi a s o C. g acili lo a we e p ima i-
ly dis ibu ed ac oss sub opical e e g een b oad-lea ed o es s in he p es-
en -day p o inces o Chongqing, Yunnan, Guizhou, Hainan, Fujian, and Zhejiang.
Table 1. Con ibu ion a e o se en bioclima ic a iables o C. g acili lo a dis ibu ion
based on he MaxEn model.
Symbol En i onmen a iable Pe cen o con ibu ion
bio14 P ecipi a ion o he d ies mon h (mm) 30.6
bio12 Annual p ecipi a ion (mm) 27.0
bio10 The mean empe a u e o he wa mes qua e (°C) 25.9
bio2 Mean diu nal ange (°C) 8.5
bio3 Iso he mali y (bio2/bio7) (×100) 4.6
bio8 The mean empe a u e o he we es qua e (°C) 2.4
bio6 Minimum empe a u e o he coldes mon h (°C) 1.0
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Ping ing Guo e al.: Dis ibu ion o Calan he g acili lo a
Figu e 3. Response cu es o C. g acili lo a p esence p obabili y o key en i onmen al a iables. No e: The ed cu es
show he a e age o e 10 eplica e uns; he blue bands show he s anda d de ia ion (SD) calcula ed o e 10 eplica es.
Figu e 4. MaxEn model achie es an ou s anding p edic ion o C. g acili lo a dis ibu ion
(AUC = 0.989). No e: AUC alues ange om 0 o 1, whe e a alue close o 1 indica es
be e classi ie pe o mance, while a alue nea 0 sugges s poo pe o mance.
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These egions exhibi ed a discon inuous dis ibu ion om wes o eas , closely
linked o he Hengduan Moun ains, Moun Wuyi, and he Taiwan Moun ains.
No ably, a wide ange o sui able egions was p esen in he sou he n sec ion
o he Hengduan Moun ains du ing his pe iod. Howe e , du ing he LGM, he
sui able egions in he sou he n Hengduan Moun ains disappea ed (Fig. 5b),
while sui able egions expanded o he Qinling Moun ains, Luoxiao Moun ains,
Figu e 5. Habi a sui abili y maps showing he occu ence o C. g acili lo a in six di e en pe iods. No e: a. LIG: Ex ensi e
sui able egions we e p esen in he sou he n sec ion o he Hengduan Moun ains, exhibi ing a discon inuous pa e n
om wes o eas ; b. LGM: The sui able egions in he sou he n sec ion o he Hengduan Moun ains disappea ed while
expanding in o he Qinling Moun ains; c. MH: The sui able egions we e o e all simila o he p esen -day dis ibu ion pa -
e n; d. Cu en : The sui able egions a e p ima ily ound in cen al and eas e n China; e. 2050s: The dis ibu ion ange o
sui able egions will gene ally sh ink; . 2070s: The o e all sui able egions inc eased compa ed wi h he p e ious pe iod,
while he highly sui able egions in Taiwan disappea ed.
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