Journal of Biogeography (1998) 25, 1029–1053 Present-day and mid-Holocene biomes reconstructed from pollen and plant macrofossil data from the former Soviet Union and Mongolia P E. T 1,2 ,T W III 3 ,A A. A 4 ,N B. A ’ 5 , N A. B 5 ,L G. B 6 ,T A. B 7 , N S. B 1 ,R C 8 ,M M. C 4 , G M. C 9 ,N I. D 10 ,V G. D 9 ,G A. E 11 , L V. F 11 ,F Z. G 12 ,J G 8 ,V S. G 1 , S P. H 2 ,D J 13 ,V I. K 14 ,E V. K 15 , I M. O 16 ,N K. P 17 , I. C P 13 ,L S 18 , D V. S 9 ,V S. V 19 and V P. Z 1 Department of Geography, Moscow State University, Vorobievy Gory, Moscow 119899, Russia (Fax:+7095 9392123), 2 Dynamic Palaeoclimatology, Lund University, Box 117, S-221 00 Lund, Sweden (Fax:+46 46 2223635), 3 Department of Geological Sciences, Brown University, Rhode Island 02912–1846, USA (Fax:+1401 8632058), 4 Institute of Geography, Russian Academy of Sciences, Staromonetny 29, Moscow 109017, Russia (Fax:+7095 2302090), 5 Department of Biology, Moscow State University, Vorobievy Gory, Moscow119899, Russia, 6 Institute of Biology, Ukrainian Academy of Sciences, Repina 2, Kiev, Ukraine, 7 Institute of Biology and Biophysics, Tomsk State University, Prospekt Lenina 36, Tomsk 634050, Russia, 8 Laboratoire de Botanique Historique et Palynologie, CNRS UA 1152, Faculte ´ de St-Je ´ro ˆme, Case 451, F-13397 Marseille cedex 20, France (Fax:+33 91 208668), 9 Department of Geography & Geoecology, St.-Petersburg University, 10 Liniya 33, St.-Petersburg 199178, Russia, 10 Institute of Evolution and Ecology, Russian Academy of Sciences, Piatnitskaya 47, Stroenie 3, Moscow 109017, Russia (Fax:+7095 9530713), 11 Institute of Biology, Russian Academy of Sciences (Karelian Branch), Pushkinskaya 11, Petrozavodsk 185610, Russia, 12 Forest Institute, Russian Academy of Sciences (Siberian Branch), Akademgorodok, Krasnoyarsk 660036, Russia, 13 Department of Plant Ecology, Lund University, Ekologihuset, So ¨lvegatan 37, S-223 62 Lund, Sweden (Fax:+46 46 2223742), 14 Institute of Limnology, Russian Academy of Sciences, Sevastyanova 9, St.-Petersburg 196199, Russia (Fax:+7812 2987327), 15 Institute of Palaeobiology, Georgian Academy of Sciences, Potomaja 4, Tbilisi 380004, Georgia (Fax:+78832 998823), 16 Central Geological Laboratory, Zvenigorodskoe Shosse 9, Moscow, Russia (Fax:+7095 4308458), 17 Forest Institute, Russian Academy of Sciences (Ural Branch) Bilimbaevskaya 32 A, Ekaterinburg 620134, Russia (Fax:+73432 520853), 18 Institute of Geology, Estonian Academy of Sciences, Estonia Avenue 7, Tallinn EE-0105, Estonia (Fax:+372 6312074), 19 Institute of Geology, Russian Academy of Sciences (Siberian Branch), Universitetskii 3, Novosibirsk 630090, Russia (Fax:+73832 351351), 20 Institute of Geological Sciences, Zhodinskaya 7, Minsk 220141, Belarus (Fax:+70172 636398) Abstract. Fossil pollen data supplemented by tree Ural Mountains temperate deciduous forest extended both northward and southward from its modern range. The macrofossil records were used to reconstruct the vegetation of the Former Soviet Union and Mongolia at 6000 years. northern limits of cool mixed and cool conifer forests were also further north than present. Taiga was reduced in Pollen spectra were assigned to biomes using the plant- functional-type method developed by Prentice et al. (1996). European Russia, but was extended into Yakutia where now there is cold deciduous forest. The northern limit of Surface pollen data and a modern vegetation map provided a test of the method. This is the first time such a broad-scale taiga was extended (as shown by increased Picea pollen percentages, and by tree macrofossil records north of the vegetation reconstruction for the greater part of northern Eurasia has been attempted with objective techniques. The present-day forest limit) but tundra was still present in north-eastern Siberia. The boundary between forest and new results confirm previous regional palaeoenvironmental studies of the mid-Holocene while providing a steppe in the continental interior did not shift substantially, and dry conditions similar to present existed in western comprehensive synopsis and firmer conclusions. West of the Mongolia and north of the Aral Sea. Key words. Biome, vegetation changes, vegetation maps, Correspondence: Dr Pavel E. Tarasov, Department of Geography, Moscow plant functional types, pollen taxa, Russia, Former Soviet State University, Vorobievy Gory, Moscow 119899, Russia. E-mail: [email protected]Union, Mongolia. 1998 Blackwell Science Ltd 1029
Transcript
Journal of Biogeography (1998) 25, 1029–1053
Present-day and mid-Holocene biomes reconstructed frompollen and plant macrofossil data from the former Soviet Unionand MongoliaP E. T1,2, T W III3, A A. A4, N B. A ’5,N A. B5, L G. B6, T A. B7,N S. B1, R C8, M M. C4,G M. C9, N I. D10, V G. D 9, G A. E11,L V. F 11, F Z. G12, J G8, V S. G1,S P. H2, D J13, V I. K14, E V. K15,I M. O16, N K. P17, I. C P13, L S18,D V. S9, V S. V19 and V P. Z1Department of Geography, Moscow State University, Vorobievy Gory, Moscow 119899, Russia (Fax:+7095 9392123),2Dynamic Palaeoclimatology, Lund University, Box 117, S-221 00 Lund, Sweden (Fax:+46 46 2223635), 3Department ofGeological Sciences, Brown University, Rhode Island 02912–1846, USA (Fax:+1401 8632058), 4Institute of Geography,Russian Academy of Sciences, Staromonetny 29, Moscow 109017, Russia (Fax:+7095 2302090), 5Department of Biology,Moscow State University, Vorobievy Gory, Moscow119899, Russia, 6Institute of Biology, Ukrainian Academy of Sciences,Repina 2, Kiev, Ukraine, 7Institute of Biology and Biophysics, Tomsk State University, Prospekt Lenina 36, Tomsk 634050,Russia, 8Laboratoire de Botanique Historique et Palynologie, CNRS UA 1152, Faculte de St-Jerome, Case 451, F-13397Marseille cedex 20, France (Fax:+33 91 208668), 9Department of Geography & Geoecology, St.-Petersburg University, 10Liniya 33, St.-Petersburg 199178, Russia, 10Institute of Evolution and Ecology, Russian Academy of Sciences, Piatnitskaya47, Stroenie 3, Moscow 109017, Russia (Fax:+7095 9530713), 11Institute of Biology, Russian Academy of Sciences(Karelian Branch), Pushkinskaya 11, Petrozavodsk 185610, Russia, 12Forest Institute, Russian Academy of Sciences(Siberian Branch), Akademgorodok, Krasnoyarsk 660036, Russia, 13Department of Plant Ecology, Lund University,Ekologihuset, Solvegatan 37, S-223 62 Lund, Sweden (Fax:+46 46 2223742), 14Institute of Limnology, Russian Academy ofSciences, Sevastyanova 9, St.-Petersburg 196199, Russia (Fax:+7812 2987327), 15Institute of Palaeobiology, GeorgianAcademy of Sciences, Potomaja 4, Tbilisi 380004, Georgia (Fax:+78832 998823), 16Central Geological Laboratory,Zvenigorodskoe Shosse 9, Moscow, Russia (Fax:+7095 4308458), 17Forest Institute, Russian Academy of Sciences (UralBranch) Bilimbaevskaya 32 A, Ekaterinburg 620134, Russia (Fax:+73432 520853), 18Institute of Geology, EstonianAcademy of Sciences, Estonia Avenue 7, Tallinn EE-0105, Estonia (Fax:+372 6312074), 19Institute of Geology, RussianAcademy of Sciences (Siberian Branch), Universitetskii 3, Novosibirsk 630090, Russia (Fax:+73832 351351), 20Institute ofGeological Sciences, Zhodinskaya 7, Minsk 220141, Belarus (Fax:+70172 636398)
Abstract. Fossil pollen data supplemented by tree Ural Mountains temperate deciduous forest extended bothnorthward and southward from its modern range. Themacrofossil records were used to reconstruct the vegetation
of the Former Soviet Union and Mongolia at 6000 years. northern limits of cool mixed and cool conifer forestswere also further north than present. Taiga was reduced inPollen spectra were assigned to biomes using the plant-
functional-type method developed by Prentice et al. (1996). European Russia, but was extended into Yakutia wherenow there is cold deciduous forest. The northern limit ofSurface pollen data and a modern vegetation map provided
a test of the method. This is the first time such a broad-scale taiga was extended (as shown by increased Picea pollenpercentages, and by tree macrofossil records north of thevegetation reconstruction for the greater part of northern
Eurasia has been attempted with objective techniques. The present-day forest limit) but tundra was still present innorth-eastern Siberia. The boundary between forest andnew results confirm previous regional palaeoenvironmental
studies of the mid-Holocene while providing a steppe in the continental interior did not shift substantially,and dry conditions similar to present existed in westerncomprehensive synopsis and firmer conclusions. West of theMongolia and north of the Aral Sea.
Key words. Biome, vegetation changes, vegetation maps,Correspondence: Dr Pavel E. Tarasov, Department of Geography, Moscowplant functional types, pollen taxa, Russia, Former SovietState University, Vorobievy Gory, Moscow 119899, Russia.
ranges of north-eastern and eastern Siberia from ≈160°EINTRODUCTION
at the north to≈110°E at the south. The political boundarygenerally corresponds to the natural limit of present-dayData from the large area of the countries of the Former
Soviet Union (FSU) and Mongolia are of major importance Pacific monsoon activity. Data from the Russian Far Eastare being compiled separately within the BIOME 6000to global palaeoenvironmental studies. The broad plains of
this area support vegetation and climate distributed in a project.generally zonal pattern and thus provide a good opportunityfor modelling and data-model comparison. Modern
Modern pollen datavegetation ranges from polar desert and tundra north of67–70°N, through a broad (1500–2500 km) forest belt A set of 844 surface pollen spectra was compiled from
published and unpublished sources (Fig. 1a). The largerdominated by the boreal conifer species, to the steppe anddeserts occupying the continental interior south of 50°N. part of this data set (471 samples) consists of primary pollen
counts including all identified taxa. This number includesStudies of the vegetation history in Russia and the FSUcountries, derived mainly from pollen analysis, date back eleven samples (core tops) from Belarus (for the references
see Table 1), fifty-eight from the Ukraine (Bezusko, personalalmost a century (Sukachev, 1906; Dokturovskii, 1918;Dokturovskii & Kudryashov, 1923). Neishtadt (1957), communication), sixty from Karelia (Elina, 1981; Elina &
Lak, 1989; Elina et al. 1994; 1995, 1998; Filimonova, 1985,Khotinskii (1977, 1984), and Peterson (1983a, 1993)compiled the available pollen data mainly from the forest 1995; personal communication; Filimonova & Elovicheva,
1988), sixteen from European Russia (Afanas’eva, personalzone of the USSR and demonstrated that large vegetationchanges occurred during the Holocene. These changes were communication; Gunova, 1975; Bolikhovskaya, 1990),
nineteen from the Ural region (Makovskii & Panova, 1977;explained in terms of regional changes in temperature andprecipitation that are related to global climate changes. Panova, 1981a, 1981b, 1982, 1986, 1990, 1991; Panova &
Korotkovskaya, 1990; Panova & Makovskii, 1991; PanovaHowever, large areas currently without forests were poorlyrepresented in these syntheses. Peterson (1983a, 1983b) also et al., 1996, 1998), ninety-four from the Russian Arctic and
Yakutia (Gitterman, 1963; Popova, 1961; Savvinova, 1975a,used isopoll maps to analyse the relationships of modern-pollen spectra to present-day vegetation. His work 1975b; Klimanov & Andreev, 1992; Tarasov et al., 1995),
twenty from Tuva (Dirksen, personal communication),supported the conclusions of numerous papers published inRussian showing that the spatial patterns in the modern ninety-one from Kazakhstan and Kirghizstan (Chupina,
1974; Sevastyanov et al., 1980; Tarasov, 1992), and 102pollen data reflect the zonal vegetation.Recently Prentice et al. (1996) developed a systematic from Mongolia (Mal’gina, 1971; Metel’tseva, personal
communication; Sokolovskaya, personal communication).method of biome reconstruction from palaeoecological dataand successfully tested it in Europe and northern Africa. To improve coverage over the western part of the FSU,
an additional 373 modern pollen spectra were derived fromThis method is designed to aid in constructing globalpalaeovegetation maps for key times during the late published data sets of digitized pollen abundances (Peterson,
1983a, 1983b, 1993). These data were previously used inQuaternary. Our study is an application of this method andis a contribution to the BIOME 6000 Project (Prentice & climate (Guiot et al., 1993; Peterson, 1993; Cheddadi et al.,
1997) and biome reconstructions (Prentice et al., 1996) forWebb, 1998), which was established in order to produceglobal palaeovegetation maps from palaeoecological data. the European part of the FSU. The number of pollen
taxa was limited to twenty-four in the digitized data setsThe purpose of this study has been to reconstruct biomedistributions at 6000 14C-years (6000 years) for the FSU (Peterson, 1993). We decided to use both data sets in order
to see how well biomization works for each of them.and Mongolia based on expanded modern and 6000 yearpollen and macrofossil data sets. The number of radiocarbon Because the pollen data came from different sources,
including prior compilations, the data were carefullydated pollen records has increased during the last 15 years,and we compiled a 6000 year data set of 216 sites: four screened to avoid duplications. Thirty-five samples were
excluded as probable duplicates, and priority was given totimes more than in the most recent compilation for 6000years by Peterson (1983a, 1993). A set of 844 surface modern those with a greater number of pollen taxa, i.e. to primary
pollen counts as opposed to digitized pollen data.pollen samples were used to check the method and to adaptit for the vegetation of northern Eurasia.
Pollen data for 6000 yearsDATA AND METHODS
We compiled a set of 216 pollen spectra that date to 6000years (±about 500 years) from different sources (Table 1).
Area of studyThe majority are published and unpublished primary dataderived from the European (EPD, Arles, France) and GlobalMost of the data come from the western and central parts
of the Former Soviet Union and Mongolia, approximating (GPD, Boulder, U.S.A.) pollen data bases (Fig. 1b). We alsoincluded thirty-six samples compiled from published pollen‘northern Eurasia’. This is mainly a rather flat area with a
zonal pattern to the vegetation. To the east is the Russian diagrams (Peterson, 1993) to improve the coverage, especiallyin the central Russian Plain and in Siberia. In each case weFar East, which extends east of the political boundaries of
Yakutia and Buriatia with Khabarovskii Krai, Primorskii selected the pollen sample closest to 6000 years in the profilerather than interpolating between pollen spectra. Most of theKrai and Amurskaya Oblast, going along the mountain
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1031
FIG. 1. Distribution of sites with (a) modern pollen data and (b) 6000 year pollen and macrofossil data. Closed circles indicate recentlycompiled sites with primary pollen data, open circles sites with digitized pollen data from Peterson (1983a, 1983b, 1993), and closed trianglessites with plant macrofossil data (Texier et al., 1997).
sites have enough radiocarbon dates to create an age model from the Russian Arctic (Table 1) with radiocarbon-datedtree macrofossils from Texier et al. (1997).by linear interpolation between bracketing dates. Pollen-
stratigraphic correlation was used to date the samples at a fewsites.Forduplicatedata,wegaveprioritytotheoriginalcounts
Biome reconstruction: the methodrather than to digitized data, as for the set of modern data.
In order to map the changes in the forest–tundra Prentice et al. (1996) developed an objective method torelate pollen taxa to plant functional types (PFTs) thatboundary at 6000 years better, we added seventeen sites
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1032 Pavel E. Tarasov et al.
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Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1033
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EP
DD
orof
eyuk
&T
aras
ov(1
998)
TA
IG46
Hud
o-N
ur3
48,1
399
,53
2060
2p(
c)4C
EP
DD
orof
eyuk
&T
aras
ov,
pers
onal
com
mun
icat
ion
STE
P47
Hud
o-N
ur8
48,1
399
,53
2060
4p(
c)1C
EP
DD
orof
eyuk
&T
aras
ov,
pers
onal
com
mun
icat
ion
STE
P48
Igar
ka67
,52
86,5
560
3p(
c)1D
Lev
kovs
kaya
etal
.(1
970)
TA
IG49
Il’in
skoe
60,0
038
,38
130
1p(
c)4D
Afa
nas’
eva
&B
erez
ina,
pers
onal
com
mun
icat
ion
CO
CO
50Im
atu
59,1
329
,43
453
p(c)
4CE
PD
/GP
DK
imm
el(1
995)
TE
DE
51Io
sipo
vo51
,20
28,0
08
2p(
c)1C
EP
DC
hern
avsk
aya
&F
ogel
(198
9)C
OM
X52
Ivan
o-49
,92
23,7
730
01
p(c)
7E
PD
Art
ushe
nko
etal
.(1
982a
)C
OM
XF
rank
ovsk
oe53
Kal
sa58
,17
27,4
538
12p(
c)1C
EP
D/G
PD
Kim
mel
(199
5)C
OC
O54
Kam
enny
iM
okh
63,5
736
,42
230
2p(
c)4C
Elin
a&
Yur
kovs
kaya
(198
8)C
OM
X55
Kar
akab
a49
,13
86,4
221
205
p(c)
1CG
eoek
olog
iya
gorn
ykh
kotl
ovin
(199
2)ST
EP
56K
aras
’e53
,03
70,2
243
56
p(c)
3DE
PD
Tar
asov
(199
2)ST
EP
57K
arda
shin
ski
46,5
232
,62
5013
p(c)
1CG
PD
Kre
men
etsk
ii(1
991)
TE
DE
58K
argi
nski
i70
,00
83,0
085
5p(
c)1C
Lev
ina
&N
ikit
in(1
973)
TU
ND
59K
aruj
arv
58,3
822
,20
3210
p(c)
1CE
PD
/GP
GSa
arse
(199
4)C
OM
X60
Kay
aksk
oe55
.13
80,9
710
04
p(c)
1CL
evin
aet
al.
(198
7)C
OC
O61
Kep
skoe
65,0
832
,17
124
2p(
c)1D
EP
DE
lina
(198
1)C
LM
X62
Kho
iba
60,6
789
,50
573
p(c)
3DK
arpe
nko
(196
6)T
AIG
63K
hom
inM
okh∗
51,2
028
,00
84
p(c)
1CE
PD
Che
rnav
skay
a&
Fog
el(1
989)
TE
DE
64K
hom
usta
kh63
,82
121,
6212
09
p(c)
1CE
PD
/GP
DA
ndre
evet
al.
(198
9)T
AIG
65K
irik
umae
57,6
727
,25
183
6p(
c)1D
EP
DSa
arse
(199
4)C
OM
X66
Koj
vusu
o61
,80
33,4
820
2p(
c)1C
EP
DE
lina,
pers
onal
com
mun
icat
ion
TE
DE
67K
omar
itsa
58,7
568
,82
406
p(c)
1CV
olko
vet
al.
(197
3)C
OC
O68
Kon
da60
,50
69,3
536
5p(
c)1C
Vol
kova
,pe
rson
alco
mm
unic
atio
nC
OC
O69
Kot
okol
52,8
310
8,17
460
5p(
c)1C
Kho
tins
kii
(197
7)T
AIG
70K
uben
skoe
61,0
033
,00
110
0p(
c)7
EP
D/G
PD
Kho
mut
ova
(197
7)C
OC
O71
Kul
ichk
ovsk
oe50
,33
24,1
220
00
p(c)
7E
PD
Bez
usko
,pe
rson
alco
mm
unic
atio
nC
OM
X72
Lad
oga
61,5
631
,34
51
p(c)
2DE
PD
/GP
DA
rsla
nov
etal
.(i
npr
ess)
TA
IG73
Lag
odeh
i41
,93
46,4
227
500
p(c)
7E
PD
Kva
vadz
e&
Efr
emov
(199
0)ST
EP
74L
adru
chie
61,0
039
,00
120
1p(
c)5D
EP
D/G
PD
Kho
mut
ova
(198
9)C
OC
O75
Lan
dsha
ftno
e64
,57
30,5
320
72
p(c)
2CE
PD
Elin
a,pe
rson
alco
mm
unic
atio
nC
OC
O76
Lar
ino
60,5
277
,68
509
p(c)
1CG
lebo
v(1
988)
TA
IG77
Leb
edin
oe60
,50
86,6
767
4p(
c)1D
Kar
penk
o(1
966)
TA
IG78
Lim
an49
,73
37,6
715
00
p(c)
7E
PD
Bez
usko
(197
3)T
ED
E79
Lis
i41
,78
44,6
867
60
p(c)
7E
PD
Kva
vadz
e&
Vek
ua(1
989)
CO
CO
80L
ochi
nsko
e53
,55
28,6
016
60
p(c)
7E
PD
Bog
del’
(198
4)C
OM
X81
Lop
atin
50,2
224
,83
200
0p(
c)7
EP
DA
rtus
henk
oet
al.
(198
2a)
CO
MX
82L
ovoz
ero
1∗68
,02
35,0
016
18
p(c)
1CE
PD
Elin
aet
al.
(199
5)C
LD
E83
Lov
ozer
o2
68,0
235
,00
160
1p(
c)1D
EP
DE
lina
etal
.(1
995)
CL
MX
84L
ugan
skoe
43,7
240
,68
2428
3p(
c)6D
EP
DK
vava
dze
etal
.(1
994)
STE
P85
Luk
ashk
inY
ar60
,33
78,4
045
13p(
c)1C
Gle
bov
(198
8)T
AIG
86L
ukas
hkin
Yar
60,3
378
,40
4510
p(c)
1CG
lebo
vet
al.
(197
4)T
AIG
87M
aard
u59
,43
25,0
032
3p(
c)2C
EP
D/G
PD
Ves
ki(1
992)
CO
MX
[con
tinu
ed]
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1034 Pavel E. Tarasov et al.
TA
BL
E1.
Con
tinu
ed
NN
Site
nam
eL
at.
Lon
.E
lev.
No.
14C
Sour
ceD
at.
Dat
aR
efer
ence
BIO
P(N
)(E
)(m
)da
tes
ofev
id.
cont
r.ba
se
88M
adja
gara
64,8
312
0,97
160
7p(
c)3D
EP
D/G
PD
And
reev
&K
liman
ov(1
989)
TA
IG89
Mak
sim
kin
Yar
58,6
585
,00
125
3p(
c)1C
Bly
akha
rchu
k(1
990)
TA
IG90
Mal
.K
heta
69,7
584
,25
422
p(c)
2CK
ind
(197
4)T
AIG
91M
ardy
-Yak
ha70
,30
67,3
65
0p(
c)7
Vol
kova
,pe
rson
alco
mm
unic
atio
nT
AIG
92M
ezhg
orno
e66
,37
30,7
019
01
p(c)
4CE
PD
Elin
a(1
981)
CO
CO
93M
ocha
zhin
a60
,33
90,0
080
8p(
c)1C
Gle
bov
&K
arpe
nko
(198
9)T
AIG
94M
oshk
arno
e1
62,2
534
,05
589
p(c)
1CE
PD
Fili
mon
ova
(199
5)C
OC
O95
Mos
hkar
noe
262
,25
34,0
558
8p(
c)1C
Fili
mon
ova
(199
5)C
OC
O96
Mos
kovs
kiy
50,5
534
,50
135
0p(
c)7
EP
DA
rtus
henk
o(1
960)
TE
DE
Bob
rik
97M
ustu
suo
61,8
133
,50
101
2p(
c)4C
EP
DE
lina
(198
1)C
OC
O98
Nar
och
54,0
026
,00
120
2p(
c)5C
EP
DY
akus
hko
etal
.(1
992)
CO
CO
99N
azin
o60
,52
77,6
845
16p(
c)1C
Gle
bov
(198
8)T
AIG
100
Nei
nasu
o66
,35
30,6
311
02
p(c)
4CE
PD
Elin
a(1
981)
TA
IG10
1N
enaz
vann
oe61
,81
33,4
810
01
p(c)
4CE
PD
Elin
a(1
981)
CO
CO
102
Ner
o27
4∗57
,17
39,4
893
0p(
c)7
EP
DG
unov
a(1
975)
CO
CO
103
Ner
o2P
57,1
739
,48
933
p(c)
1CE
PD
Gun
ova
(197
5)C
OM
X10
4N
igul
a58
,00
24,6
755
11p(
c)1C
EP
D/G
PD
Sarv
&Il
ves
(197
6)T
ED
E10
5N
ikul
ino-
160
,50
86,6
759
4p(
c)3D
Gle
bov,
pers
onal
com
mun
icat
ion
TA
IG10
6N
ikul
ino-
260
,50
86,6
771
1p(
c)4D
Gle
bov,
pers
onal
com
mun
icat
ion
TA
IG10
7N
jukh
chin
skii
63,9
236
,30
201
p(c)
4DE
PD
Elin
a(1
981)
TA
IGM
okh
108
Nus
uo64
,57
30,8
316
31
p(c)
4CE
PD
Elin
a(1
981)
CO
MX
109
Now
yG
utis
ki50
,27
26,8
321
00
p(c)
7E
PD
Art
ushe
nko
etal
.(1
982a
)C
OM
X11
0N
ulsa
veit
o67
,67
70,1
755
5p(
c)1C
Pan
ova
(199
0)T
AIG
111
One
go6
61,7
234
,92
330
p(c)
7E
PD
/GP
DK
hom
utov
a(1
976)
TA
IG11
2O
nego
861
,72
34,9
233
0p(
c)7
EP
D/G
PD
Kho
mut
ova
(197
6)T
AIG
113
Oso
yevk
a50
,90
35,2
216
00
p(c)
7E
PD
Bez
usko
(197
3)C
OM
X11
4O
svea
56,0
528
,08
129
0p(
c)7
EP
DZ
erni
tska
ya,
pers
onal
com
mun
icat
ion
CO
MX
115
Oze
rki
50.4
280
,47
210
9p(
c)1C
EP
DT
aras
ov(1
992)
STE
P11
6P
aana
jarv
i66
,27
29,9
513
71
p(c)
4CE
lina
etal
.(1
994)
CO
CO
117
Pai
dre
58,2
725
,63
513
p(c)
1CE
PD
/GP
DSa
arse
,19
94;
Saar
seet
al.
(199
5)C
OM
X11
8P
ashe
nnoe
49,3
775
,40
871
14p(
c)1C
EP
DT
aras
ov(1
992)
STE
P11
9P
elis
oo58
,47
22,3
833
5p(
c)3C
EP
D/G
PD
Saar
se(1
994)
CO
MX
120
Pes
chan
oe51
,98
25,4
813
90
p(c)
7E
PD
Zer
nits
kaya
(198
9)T
ED
E12
1P
esch
anoe
(Ura
l)56
,90
60,3
231
00
p(c)
7P
anov
a&
Kor
otko
vska
ya(1
990)
CO
CO
122
Pet
rilo
vo56
,00
31,9
817
51
p(c)
4CE
PD
/GP
DG
unov
a&
Siri
n(1
995)
CO
MX
123
Pet
ropa
vlov
skii
58,3
383
,00
125
4p(
c)3D
Bly
akha
rchu
k(1
990)
TA
IG12
4P
it-G
orod
ok59
,25
93,8
045
1p(
c)7
Kin
d(1
974)
TA
IG12
5P
olon
ichk
a50
,27
24,7
520
00
p(c)
7E
PD
Art
ushe
nko
etal
.(1
982a
)C
OM
X12
6P
opov
schi
na50
,42
34,0
013
50
p(c)
7E
PD
Bez
usko
(197
3)T
ED
E12
7P
tich
je66
,35
30,5
712
02
p(c)
3DE
PD
Elin
a(1
981)
CO
CO
128
Pun
so57
,68
27,2
518
312
p(c)
1CE
PD
/GP
DSa
arse
(199
4)C
OM
X12
9P
ur-T
az66
,70
79,7
360
5p(
c)1C
And
reev
,pe
rson
alco
mm
unic
atio
nT
AIG [c
onti
nued
]
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1035
TA
BL
E1.
Con
tinu
ed
NN
Site
nam
eL
at.
Lon
.E
lev.
No.
14C
Sour
ceD
at.
Dat
aR
efer
ence
BIO
P(N
)(E
)(m
)da
tes
ofev
id.
cont
r.ba
se
130
Qua
rtze
voe
43,6
741
,17
2726
1p(
c)6D
EP
DK
vava
dze
&E
frem
ov(1
996)
STE
P13
1R
aiga
stve
re58
,60
26,7
352
11p(
c)1C
EP
D/G
PD
Pir
rus,
Rou
k&
Liiv
a(1
987)
CO
MX
132
Rit
tusu
o61
,77
33,5
520
1p(
c)4C
Elin
a,pe
rson
alco
mm
unic
atio
nC
OC
O13
3R
udus
hsko
e56
,50
27,5
515
01
p(c)
4CE
PD
Kho
mut
ova
(198
9)C
OM
X13
4R
ugoz
ero
64,0
832
,63
140
2p(
c)2C
EP
DE
lina
(198
1)C
OC
O13
5S1
9kst
rm57
,00
40,0
012
70
p(c)
7E
PD
/GP
DO
sipo
va,
pers
onal
com
mun
icat
ion
CO
MX
136
S269
saht
56,0
039
,00
150
0p(
c)7
Osi
pova
,pe
rson
alco
mm
unic
atio
nC
OM
X13
7Sa
lekh
ard
66,5
566
,58
52
p(c)
2CV
olko
va,
pers
onal
com
mun
icat
ion
TA
IG13
8Sa
man
don-
70,7
813
6,26
107
p(c)
1DE
PD
/GP
DV
elic
hko,
And
reev
&K
liman
ov(1
994)
TU
ND
Kaz
ach’
e13
9Sa
mba
lsko
e61
,77
34,1
512
045
p(c)
1CE
lina,
Ars
lano
v&
Klim
anov
(199
6)C
OM
X14
0Sa
viku
58,4
227
,24
306
p(c)
1CE
PD
/GP
DSa
rv&
Ilve
s(1
975)
CO
MX
141
Sebb
olot
o64
,67
43,3
365
1p(
c)4C
Yur
kovs
kaya
,E
lina
&K
liman
ov(1
989)
;C
OM
XY
urko
vska
ya&
Elin
a(1
991)
142
Sely
ahi
51,8
323
,75
154
0p(
c)7
EP
DZ
erni
tska
ya(1
991)
TE
DE
143
Sern
y43
,67
40,4
824
852
p(c)
5DE
PD
Kva
vadz
e&
Efr
emov
(199
5)ST
EP
144
Shir
et-N
ur46
,53
101,
8225
003
p(c)
3CE
PD
Dor
ofey
uk&
Tar
asov
,pe
rson
alco
mm
unic
atio
nST
EP
145
Shom
bash
uo1
65,1
232
,98
100
2p(
c)1C
EP
DE
lina
(198
1)C
OC
O14
6Sh
omba
shuo
265
,12
32,9
899
2p(
c)2C
Elin
a,pe
rson
alco
mm
unic
atio
nC
OC
O14
7So
leno
e47
,90
46,1
7−
194
p(c)
3CB
olik
hovs
kaya
(199
0)C
OM
XZ
aim
ishc
he14
8So
loki
ya50
,42
24,1
719
00
p(c)
7E
PD
Art
ushe
nko
etal
.(1
982a
)C
LD
E14
9So
svya
tsko
e56
,20
32,0
017
51
p(c)
4CE
PD
/GP
Gun
ova
&Si
rin
(199
5)C
OM
X15
0St
arni
ki50
,27
26,0
219
810
p(c)
1CE
PD
Bez
usko
,K
liman
ov&
Shel
yag-
Sose
nko
(198
8)C
OM
X15
1St
av50
,42
35,4
015
50
p(c)
7E
PD
Bez
usko
(197
3)ST
EP
152
Stoy
anov
-150
,38
24,6
319
80
p(c)
7E
PD
Bez
usko
,pe
rson
alco
mm
unic
atio
nC
OM
X15
3St
oyan
ov-2
50,3
824
,63
198
8p(
c)1C
EP
DB
ezus
ko,
Klim
anov
&Sh
elya
g-So
senk
o(1
988)
CO
MX
154
Stup
ino
52,2
539
,83
951
p(c)
3DE
PD
Che
rnav
skay
a,pe
rson
alco
mm
unic
atio
nC
LM
X15
5Su
dobl
e54
,03
28,6
016
58
p(c)
1DE
PD
Bog
del’
etal
.(1
983)
CO
MX
156
Surg
ut61
,23
73,3
340
5p(
c)1C
Nei
shta
dt(1
976)
TA
IG15
7Sv
itja
z53
,70
28,6
824
20
p(c)
7E
PD
Bog
del’
(198
4)T
ED
E15
8Sv
jato
e54
,00
31,2
319
50
p(c)
7E
PD
Bog
del’
(198
4)T
ED
E15
9Sv
yato
ye-2
51,1
024
,33
183
0p(
c)7
EP
DA
rtus
henk
o(1
957)
TE
DE
160
Tan
ino
ozer
o58
,00
85,0
012
58
p(c)
1CB
lyak
harc
huk
(199
0)T
AIG
161
Teg
ul’d
etsk
ii57
,00
89,0
012
53
p(c)
1DB
lyak
harc
huk
(199
0)T
AIG
162
Ter
khiin
-Tsa
gan-
48,1
599
,70
2060
8p(
c)1C
Dor
ofey
uk&
Tar
asov
,pe
rson
alco
mm
unic
atio
nST
EP
Nur
816
3T
om’
56,8
384
,45
856
p(c)
1CA
rkhi
pov
&V
otak
h(1
980)
TA
IG16
4U
rmiin
-Tsa
gan-
48,8
410
2,93
1450
2p(
c)1C
Dor
ofey
uk&
Tar
asov
,pe
rson
alco
mm
unic
atio
nST
EP
Nur
165
Ust
’M
ash
56,3
257
,88
220
5p(
c)1C
Pan
ova,
Mak
ovsk
ii&
Ero
khin
(199
6)C
OC
O16
6V
erhi
51,8
528
,80
146
2p(
c)6D
EP
DZ
erni
tska
ya(1
986)
TE
DE
167
Vis
hnev
skoe
60,5
029
,52
151
p(c)
2DE
PD
Ars
lano
vet
al.
(199
2)C
LM
X
[con
tinu
ed]
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1036 Pavel E. Tarasov et al.
TA
BL
E1.
Con
tinu
ed
NN
Site
nam
eL
at.
Lon
.E
lev.
No.
14C
Sour
ceD
at.
Dat
aR
efer
ence
BIO
P(N
)(E
)(m
)da
tes
ofev
id.
cont
r.ba
se
168
Vod
oraz
del
59,3
876
,90
101
17p(
c)1C
Gle
bov
etal
.(1
997)
TA
IG16
9V
ohm
a59
,05
27,3
346
14p(
c)1C
EP
D/G
PD
Kim
mel
(199
5)C
OM
X17
0Y
aman
t-N
ur49
,90
102,
6010
001
p(c)
7E
PD
Dor
ofey
uk&
Tar
asov
,pe
rson
alco
mm
unic
atio
nC
LD
E17
1Y
enis
ei68
,17
87,1
510
06
p(c)
1DA
ndre
ev,
pers
onal
com
mun
icat
ion
TA
IG17
2Z
aboi
noe
55,5
362
,37
275
0p(
c)7
EP
DK
hom
utov
a,pe
rson
alco
mm
unic
atio
nT
AIG
173
Zal
ozci
-249
,75
25,4
532
015
p(c)
1CE
PD
Art
ushe
nko
etal
.(1
982a
)C
OC
O17
4Z
amos
hje
62,0
535
,20
404
p(c)
1CE
lina,
pers
onal
com
mun
icat
ion
CO
CO
175
Zap
oved
noe
65,1
232
,63
110
2p(
c)4C
EP
DE
lina
(198
1)C
OC
O17
6Z
arut
skoe
63,9
036
,25
205
p(c)
1CE
PD
Elin
a(1
981)
CO
CO
177
Zdi
tovo
52,6
025
,55
147
1p(
c)4C
EP
DZ
erni
tska
ya&
Dai
neko
(198
6)C
LM
X17
8Z
urat
kul’
54,9
059
,27
720
0p(
c)7
Pan
ova
(198
2)C
OC
O17
9A
iats
koe
57,0
060
,08
229
7p(
d)1C
Pet
erso
on(1
993)
CO
MX
180
Ara
lSe
a46
,67
61,5
077
0p(
d)7
Pet
erso
n(1
993)
DE
SE18
1B
.71
,07
156,
5077
4p(
d)1C
Pet
erso
n(1
993)
TU
ND
Kur
opat
ochy
a18
2B
alka
shki
nski
i53
,03
35,3
777
2p(
d)7
Pet
erso
n(1
993)
CO
MX
183
Beg
lians
kii
Ria
m55
,50
81,5
777
0p(
d)7
Pet
erso
n(1
993)
TA
IG18
4B
elka
chi
59,1
513
1,98
458
0p(
d)7
Pet
erso
n(1
993)
TU
ND
185
Bol
.P
ersh
ino
59,3
569
,00
772
p(d)
4CP
eter
son
(199
3)T
AIG
186
Chu
nia
61,7
510
2,80
229
1p(
d)4C
Pet
erso
n(1
993)
TA
IG18
7D
avsh
e54
,33
110,
0345
88
p(d)
1CP
eter
son
(199
3)T
AIG
188
Glu
khar
inoe
66,0
069
,00
770
p(d)
7P
eter
son
(199
3)T
AIG
189
Iam
sove
i65
,67
78,2
577
0p(
d)7
Pet
erso
n(1
993)
TA
IG19
0Im
nats
koe
42,0
841
,72
458
4p(
d)1C
Pet
erso
n(1
993)
TE
DE
191
Iuri
bei
69,0
070
,00
770
p(d)
7P
eter
son
(199
3)C
LD
E19
2Iv
anov
skoe
356
,83
39,0
077
2p(
d)2C
Pet
erso
n(1
993)
CO
MX
193
Kra
deno
e62
,00
129,
5822
94
p(d)
1CP
eter
son
(199
3)T
AIG
194
Lak
htin
skoe
60,0
030
,17
773
p(d)
4CP
eter
son
(199
3)C
OC
O19
5M
arkh
ida
67,1
752
,55
772
p(d)
2CP
eter
son
(199
3)T
AIG
196
Mul
iank
a57
,78
56,3
222
91
p(d)
5CP
eter
son
(199
3)C
OC
O19
7M
yksi
58,1
524
,97
776
p(d)
1CP
eter
son
(199
3)C
OM
X19
8N
izhn
e-V
arto
vsk
60,9
376
,63
7713
p(d)
1CP
eter
son
(199
3)T
AIG
199
Ors
hins
kii
Mok
h56
,95
35,9
577
3p(
d)2C
Pet
erso
n(1
993)
CO
MX
200
Ose
chen
skoe
57,5
234
,83
229
6p(
d)1C
Pet
erso
n(1
993)
CO
MX
201
Pad
en’g
a62
,80
42,9
377
0p(
d)7
Pet
erso
n(1
993)
CO
CO
202
Pol
ovet
sko-
57,5
737
,90
772
p(d)
5CP
eter
son
(199
3)C
OM
XK
upan
skoe
203
R.
B.
70,7
598
,60
773
p(d)
2CP
eter
son
(199
3)T
AIG
Rom
anik
ha20
4Sa
khty
sh1
56,8
040
,42
770
p(d)
7P
eter
son
(199
3)C
OM
X20
5Sa
rtyn
ia64
,17
65,4
777
0p(
d)7
Pet
erso
n(1
993)
CO
CO
206
Sele
rika
n64
,30
141,
8745
82
p(d)
2CP
eter
son
(199
3)T
UN
D20
7Sh
uval
ovsk
oe60
,05
30,3
377
7p(
d)1C
Pet
erso
n(1
993)
CO
MX
[con
tinu
ed]
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1037
TA
BL
E1.
Con
tinu
ed
NN
Site
nam
eL
at.
Lon
.E
lev.
No.
14C
Sour
ceD
at.
Dat
aR
efer
ence
BIO
P(N
)(E
)(m
)da
tes
ofev
id.
cont
r.ba
se
208
Som
ino
56,6
038
,80
776
p(d)
4CP
eter
son
(199
3)C
OM
X20
9So
rt68
,83
148,
000
2p(
d)2C
Pet
erso
n(1
993)
TU
ND
210
Tes
ovo-
58,9
230
,90
776
p(d)
1CP
eter
son
(199
3)C
OM
XN
etyl
’sko
e21
1T
iuliu
ksko
e54
,67
59,1
745
80
p(d)
7P
eter
son
(199
3)C
OC
O21
2T
ugiy
an-Y
ugan
63,5
565
,72
7710
p(d)
5CP
eter
son
(199
3)T
AIG
213
Ubi
nski
iri
am55
,32
80,0
077
0p(
d)7
Pet
erso
n(1
993)
TA
IG21
4U
lano
vo55
,55
48,7
277
0p(
d)7
Pet
erso
n(1
993)
CL
MX
215
Vak
haru
58,8
524
,78
7710
p(d)
2CP
eter
son
(199
3)C
OM
X21
6V
asiu
gan’
eI
56,8
783
,08
771
p(d)
7P
eter
son
(199
3)T
AIG
217
B.
Bal
akhn
ia73
,25
100,
7250
1m
3DT
exie
ret
al.,
(199
7)C
LD
E21
8B
.B
alak
hnia
73,3
010
2,63
501
m1D
Tex
ier
etal
.,(1
997)
CL
DE
(A-3
18)
219
B.
Bal
akhn
ia-2
773
,37
104,
3550
1m
2DT
exie
ret
al.,
(199
7)C
LD
E22
0B
.B
alak
hnia
-28
73,4
310
0.52
501
m2D
Tex
ier
etal
.,(1
997)
CL
DE
221
B.
Bal
akhn
ia-2
973
,31
100,
5350
1m
2DT
exie
ret
al.,
(199
7)C
LD
E22
2B
.R
oman
ikha
70,8
299
,08
501
m1D
Tex
ier
etal
.,(1
997)
CL
DE
(XX
-44)
223
Kar
gins
kii
69,9
583
,58
501
m1D
Tex
ier
etal
.,(1
997)
TA
IG22
4K
hata
nga
72,7
810
4,63
501
m1D
Tex
ier
etal
.,(1
997)
CL
DE
225
Khe
ta70
,63
94,7
550
1m
1DT
exie
ret
al.,
(199
7)C
LD
E22
6L
adon
nakh
G-
72,0
096
,33
501
m2D
Tex
ier
etal
.,(1
997)
CL
DE
119
227
M.
Bal
akhn
ia72
,75
103,
0050
1m
3DT
exie
ret
al.,
(199
7)C
LD
E22
8M
alay
aK
heta
69,5
784
,53
501
m1C
Tex
ier
etal
.,(1
997)
TA
IG22
9M
osun
72,7
810
4,22
501
m3D
Tex
ier
etal
.,(1
997)
CL
DE
230
Nov
aya-
M.
72,5
510
3,50
501
m1D
Tex
ier
etal
.,(1
997)
CL
DE
Bal
akhn
ia23
1P
ukhu
chay
akha
71,4
367
,96
501
m3D
Tex
ier
etal
.,(1
997)
CL
DE
232
Zak
haro
va72
,78
101,
6250
1m
1DT
exie
ret
al.,
(199
7)C
LD
ER
asso
kha
(I-1
56)
233
Zap
.T
aim
yr74
,53
100.
5050
1m
1DT
exie
ret
al.,
(199
7)C
LD
E
1.W
hen
mor
eth
anon
eco
reis
avai
labl
efr
omth
esa
me
site
the
core
wit
hbe
tter
dati
ngco
ntro
lha
sbe
enus
edfo
rm
appi
ngpu
rpos
es.
How
ever
,co
res
mar
ked
bya
star
are
not
used
inF
ig.
3(d)
.2.
Sour
ceof
data
isin
dica
ted
by‘p
(c)’
for
new
com
pile
dpr
imar
ypo
llen
data
,by
‘p(d
)’fo
rdi
giti
zed
polle
nda
taan
dby
‘m’
for
plan
tm
acro
foss
ilda
ta.
3.D
atin
gco
ntro
lis
am
easu
reof
the
accu
racy
ofth
eid
enti
ficat
ion
ofth
e60
00ye
arti
me-
slic
ean
dm
akes
use
ofsc
hem
esfo
rco
ntin
uous
(C)
and
disc
onti
nuou
s(D
)re
cord
sas
give
nin
Tar
asov
etal
.(1
996)
.F
orco
ntin
uous
reco
rds,
a1C
inth
eda
ting
cont
rol
colu
mn
indi
cate
sth
atth
ere
are
two
brac
keti
ngra
diom
etri
cda
tes
each
wit
hin
2000
year
sof
6000
year
s,
whe
reas
2C,
3C,
4Can
d5C
indi
cate
two
brac
keti
ngda
tes
wit
hin
2000
and
4000
;40
00an
d40
00;
4000
and
6000
;60
00an
d60
00ye
ars
of60
00ye
ars
,
resp
ecti
vely
.fo
rdi
scon
tinu
ous
reco
rds,
1D,
2D,
3D,
4D,
5D,
and
6Din
dica
tea
radi
omet
ric
date
wit
hin
250,
500,
750,
1000
,15
00an
d20
00ye
ars,
resp
ecti
vely
,of
6000
year
s.
A7
inth
eda
ting
cont
rol
colu
mn
indi
cate
sth
atth
ere
cord
sar
epo
orly
date
d.4.
Dat
aba
sew
here
the
polle
nda
taar
ecu
rren
tly
plac
ed:
EP
D–
Eur
opea
nP
olle
nD
ata
Bas
e(A
rles
,F
ranc
e);
GP
D–
Glo
bal
Pol
len
Dat
aB
ase
(Bou
lder
,U
.S.A
.).
5.B
IOP
–po
llen-
deri
ved
biom
esat
6ka
,w
here
TU
ND=
tund
ra,
TA
IG=
taig
a,C
LD
E=
cold
deci
duou
sfo
rest
,C
OC
O=
cool
confi
erfo
rest
,C
LM
X=
cold
mix
edfo
rest
,C
OM
X=
cool
mix
edfo
rest
,T
ED
E=
tem
pera
tede
cidu
ous
fore
st,
STE
P=
step
pe,
and
DE
SE=
dese
rt.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1038 Pavel E. Tarasov et al.
group taxa by their stature, leaf form, phenology, and We also defined several new PFTs in an attempt toincrease the number of taxa available for identification ofbioclimatic tolerance. The method has been successfully
applied to the modern and 6000-year pollen data from forest biomes.Europe (Prentice et al., 1996), western and eastern Africa
1. Pinus pumila (Pall.) Regel, a shrub-like form of Pinus(Jolly et al., 1998), eastern North America (Summers et al.,
subgen. Haploxylon, can survive under the snow cover1998), and China (Yu et al., 1998).
in the cold continental climate of eastern Siberia withThe procedure for reconstructing biomes from pollen
mean coldest-month temperature below −35 °Cdata known as ‘biomization’ is based on a fuzzy logic
(Klimaticheskii Atlas SSSR, 1960). This taxon wasapproach in which all pollen spectra are supposed to have
assigned to a ‘cool-boreal conifer’ type.an ‘affinity’ for every biome and the affinity is expressed in
2. A number of deciduous shrubs (e.g. Lonicera, Sambucus,terms of a numerical score. The key steps are (1) assignment
Viburnum) have a range spanning the distribution of bothof each pollen taxon to one or more PFTs according to its
temperate and boreal summergreen trees (Hulten & Fries,biology; (2) assignment of characteristic PFTs to biomes
1986). We classified these as ‘boreal-temperate summer-according to their bioclimatic range and actual distribution;
green’.(3) construction of a biome by taxon matrix illustrating
3. Rubus chamaemorus L. was defined as an ‘arctic-borealwhich taxa may occur in each biome; (4) calculation of the
dwarf shrub’ since it acts both as an arctic-alpine dwarfaffinity scores for all pollen samples by
shrub and as a common understorey or mire plant inthe boreal forest (Hulten & Fries, 1986).
Aik=RjdijJ{max[0, (pjk−hj)]} (1) 4. Russian studies of pollen morphology (Kupriyanova,1965; Kupriyanova & Aleshina, 1972) demonstrated thatthe pollen of dwarf birch (Betula nana L., sensu lato)where Aik is the affinity of pollen sample k for biome i;and shrub alder (Alnus fruticosa Rupr.) can generally besummation is over all taxa j; d ij is the entry in thedistinguished from the corresponding tree forms (e.g.biome×taxon matrix for biome i and taxon j; pjk are theBetula sect. Albae, Alnus glutinosa (L.) Gaertner, Alnuspollen percentages, and hj is a threshold pollen percentageincana (L.) Moench). Where these distinctions were made,(0.5% in this paper, following Prentice et al. (1996)). Forwe were able to assign these taxa to appropriate PFTs.each pollen sample, the biome with the highest score is
assigned. Several further modifications were made to the treatmentof nonarboreal PFTs.
Assignment of pollen taxa to plant functional types 1. We increased the number of taxa assigned to steppe forbs(PFTs) and PFTs to biomes and desert forbs compared to Prentice et al. (1996) to
improve the distinction between tree and tree-less biomesIn their initial study, Prentice et al. (1996) used the published
and among the herbaceous biomes themselves. The samedata set of surface pollen samples from Guiot, Harrison &
kind of empirical decisions as in Prentice et al. (1996)Prentice (1993) to test the biomization method for the area
were made for the nonarboreal taxa. Most of them canof ‘biogeographical Europe’ west of 60°E. A limited number
appear in each biome, but certain taxa have a usefulof taxa were available in this data set, and these were
diagnostic value. For example, Rubiaceae andassigned to one or several PFTs using the PFT classification
Caryophyllaceae have higher percentages in steppe, asdescribed in Prentice et al. (1992). The results of this study
do Ephedra in desert and Cyperaceae in tundra.were good in terms of recovering the broad distribution of
2. Artemisia and Chenopodiaceae were included in bothbiomes. Prentice et al. (1996), however, noted that a
steppe-forb and desert-forb PFTs because they oftenrestriction in the agreement between actual and
codominate in both the steppe and desert environmentsreconstructed biomes may occur because many minor pollen
(Walter, 1985).taxa (mainly herbaceous) were not listed in their surface
3. We allowed Poaceae to be characteristic in the tundradata set (Prentice et al., 1996). This limitation could be a
and steppe biomes where grasses grow and are a keymajor problem in central Eurasia where tree-less biomes
taxon, but we excluded Poaceae from the desert biome.(tundra, steppe and desert) are more important than in
In Europe, Prentice et al. (1996) also placed this taxonEurope. Having a chance to use both primary pollen counts
in the desert biome. However, desert is only a minorand digitised pollen percentages, we decided to start with
biome in Europe so the accuracy of assignment to desertthe same assignment of pollen taxa to PFTs and PFTs to
was not well tested.biomes as Prentice et al. (1996) used and then modify theassignment by paying special attention to taxa not presented Biomes were then characterized in terms of the newly
adopted PFTs (Table 3). Data from Tables 2 and 3 providein their scheme. Table 2 lists all available pollen taxa in theset of modern surface samples and shows the set of PFTs a basis for constructing a biome-taxon matrix used for the
calculation of the affinity scores. We followed Prentice et al.to which they were assigned. After exclusion of aquatic taxa(e.g. Typha, Potamogeton, Sparganium, etc.), taxa (1996) and used the universal threshold of 0.5% for pollen
percentages. Biomes were identified in the order that theyrepresented by only one grain (e.g. Oxalis), exotic taxa(e.g. Tsuga), and taxa restricted to local microhabitats (e.g. appear in Table 3. This order does not play any role in the
choice among species-rich biomes, or biomes with well-Drosera, Scheuchzeria, Geum), the remaining taxa were usedin assigning biomes to the pollen samples (Table 2). represented indicator taxa in the pollen assemblage. The
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Biomes from the FSU and Mongolia 1039
TABLE 2. Plant functional types and the pollen taxa assigned to them.
TABLE 3. FSU and Mongolian biomes and their characteristic plant functional tupes (PFTs) PFTs inparentheses are restricted to part of their biome. Abbreviations for PFTs as in Table 2.
order becomes important when biomes are represented by woody remains from the now tree-less Arctic region. Weassume that the presence even of a single tree stump, barkonly a few broadly distributed taxa (e.g. cold deciduous or
cold mixed forest) where some biomes are distinguished fragment, cone or needle at sites north of the present-daytree line indicates a shift in the forest boundary and canonly by the absence of one or more of these taxa.therefore help to define the boundary between tundra andforest. In cases when only a single arboreal macrofossil was
Extension of the method to plant macrofossil datarecorded we took it as 100%. If more than one arborealtaxon was identified then each was assigned an equalA similar biomization procedure was applied to the
radiocarbon-dated plant macrofossils, which are mainly proportion. The order of biomes, as discussed before, play
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1040 Pavel E. Tarasov et al.
TABLE 4. Simplified vegetation types used in the Fiziko-Geograficheskii Atlas Mira (1964) and their allocation to the biomes used byPrentice et al. (1992)
Biome name Vegetation type
Tundra Arctic tundraMoss-lichen, dwarf shrub and sedge tundraMountain arctic and subarctic tundra
Cold deciduous forest Larch taiga-like forestBirch and larch-birch thin forest (forest-tundra)Pinus pumila shrubby weedsPoplar-birch and pine forests of western SiberiaPine-birch forests of Kazakhstan and Mongolia
Taiga “Dark” conifer (taiga) forest with Picea, Abies and Pinus sibiricaPine and pine-larch forests (with Pinus sibirica)Spruce-birch and spruce-larch thin forests (forest-tundra)
Broad-leaved evergreen/warm mixed forest Broad-leaved forest with subtropical elements (western Caucasus)Steppe Meadow-steppe and steppe-meadows (forest-steppe)
Graminoid (typical) steppeAlpine and subalpine meadowArtemisia–graminoid desertic steppe (semidesert)Mountain and submountain steppe
Desert Artemisia, chenopod and ephemeral-wormwood shrub desertsHaloxylon persicum and H. ammodendron tree-shrub and shrub desertHigh-altitude Artemisia and dwarf shrub desert
a key role for the biomization of tree macrofossil data. Table 4 we have simply assigned this vegetation type tocold deciduous forest.Thus the presence of only a temperate summergreen tree
(e.g. Betula or Larix) gives priority to the cold deciduousforest biome, but the presence of a boreal conifer as well
RESULTS(e.g. Picea) results in assignment to the taiga biome. Thissimple diagnostic approach based on limited data works
Mapped patterns in the pollen datawell for regions where the forest vegetation is characterizedby only a few species, belonging to one or two PFTs. Figure 2 indicates some of the geographical patterns in
pollen abundance that provide the basis for reconstructedbiome distributions and their changes from 6000 years to
Testing the method with modern pollen datapresent. The present-day pollen abundances (Fig. 2a) showstrong geographical patterns that clearly reflect the zonalVegetation descriptions for the modern pollen samples with
primary counts were obtained from site descriptions and vegetation pattern. Picea is strongly represented throughoutthe modern taiga (including high-elevation sites in the centralwere derived from vegetation maps of the USSR and
Mongolia (Fiziko-Geograficheskii Atlas Mira, 1964) for the Asian mountains). Cool-temperate summergreen andtemperate summergreen taxa are confined to the westernother sites.
Biome reconstructions based on the modern pollen part and are abundant in the deciduous forest zone(including the belt of deciduous forest that lies between thesamples were then compared with vegetation assignments
on a site-by-site basis. The names of the vegetation types taiga and the steppe). The cool-temperate taxa extendfurther north, with moderate abundances also in the coolin the Russian botanical literature are different from the
biome names used in this paper, but it was easy to assign mixed forest zone. Artemisia and Chenopodiaceae have highabundances in the steppe and desert zones of south-easternthese vegetation types to biomes (Table 4). The only problem
was to identify the cold mixed forest biome as shown by Europe and central Asia as well as in the steppe-likevegetation of interior Yakutia. Poaceae have high pollenPrentice et al. (1992) in the discontinuous belt along the
forest-steppe transition east of the Urals, where there are abundances primarily in the steppes but also in the Arctictundra. Moderate and variable abundances of Poaceae alsoin fact woodlands with Pinus, Populus and Betula. This
vegetation type occupies a relatively small area in northern appear throughout the European part, probably mainly asa result of human impact in agricultural areas.Eurasia and has no well-represented indicative taxa to
separate it from cold deciduous forests. In the map of Broadly similar patterns are observed for 6000 years(Fig. 2b) but with certain important differences. Picea showspresent vegetation at the sampling sites (Fig. 3b) and in
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1041
FIG
.2.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1042 Pavel E. Tarasov et al.
FIG
.2.
Map
ped
tota
lab
unda
nces
ofse
lect
edta
xaor
PF
Ts:
(a)
inm
oder
npo
llen
sam
ples
,(b
)in
6000
year
polle
nsa
mpl
es.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1043
TABLE 5. Numerical comparison for each site between biomes derived from modern surface samples (indexed by a “p”) for whichprimary pollen data was available and observed biomes (indexed by an “a”). (TUND=tundra, TAIG=taiga, CLDE-cold deciduous forest,COCO=cool conifer forest, COMX=cool mixed forest, TEDE=temperate deciduous forest, STEP=steppe, DESE=desert).
TABLE 6. Numerical comparison for each site between biomes derived from modern surface samples (indexed by a “p”) for which digitisedpollen data was available and observed biomes (indexed by an “a”). (TUND=tundra, TAIG=taiga, CLDE=cold deciduous forest,COCO=cool conifer forest, CLMX=cold mixed forest, COMX=cool mixed forest, TEDE=temperate deciduous forest, WAMX=warmmixed forest, STEP=steppe, DESE=desert).
a slight increase in pollen abundances and areal extent in the available modern pollen samples (Fig. 3a) and separatelythe far north (at least in the western half of the region), for the data set, which includes samples with primary countsand is somewhat more abundant in the eastern interior of and forty-seven digitized samples (Peterson, 1993) in whichSiberia. Cool-temperate summergreen taxa also show a dwarf shrub- and tree-forms of Betula and Alnus weredistinct northward expansion in eastern Europe, while pollen separated (Fig. 3c). The comparison of the observed andof both cool-temperate and temperate summergreen taxa reconstructed vegetation shows the following.also were found at locations further south than present inwhat is now the steppe zone. Artemisia and Chenopodiaceae
1. The tree-less biomes (e.g. desert, steppe and tundra) areshow little change between 6000 years and present exceptreconstructed well. Few samples in these regions arefor generally lower than present abundances in the steppeclassified as being from forest biomes. The use ofzone of eastern Europe.additional nonarboreal taxa with positive indicator valuecontributed to this success. Often, however, steppe was
Comparison of actual and reconstructed biomes for reconstructed where the vegetation map shows desert.the present This discrepancy occurs systematically when the modern
surface samples were collected in large river valleys (e.g.The results of this comparison are shown separately for theVolga, Ural, Amu-Darya) or close to fresh-water lakesraw (Table 5) and digitized (Table 6) pollen data sets. The(e.g. Balkhash, Chatyrkel). River samples yield the sameresults show that 81% of the biomes are correctly predictedtype of bias in the tundra where forest biomes (e.g.in reconstructions based on primary pollen data as opposedtaiga or cold deciduous forest) are reconstructed. Theseto only 69% correctly predicted using digitized data. Thediscrepancies, which reflect the growth of trees incontrast is even more pronounced in the reconstruction ofprotected microhabitats, show that the biomizationtree-less biomes: the percentages of sites correctly identifiedmethod works well for reconstructing the localare 29% v. 24% for desert, 97% v. 51% for steppe, and 72%vegetation, when its pollen dominates in a surface sample.v. 43% for tundra.
Maps of pollen-derived biomes were produced for all of No problem will arise when fossil pollen samples are
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1044 Pavel E. Tarasov et al.
FIG
.3.
FIG
.3.
FIG
.3.
FIG
.3.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1045
FIG
.3.
FIG
.3.
FIG
.3.
FIG
.3.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1046 Pavel E. Tarasov et al.
FIG
.3.
FIG
.3.
FIG
.3.
FIG
.3.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1047
FIG
.3.
Dis
trib
utio
nof
(a)
polle
n-de
rive
dbi
omes
atpr
esen
t,(b
)pr
esen
tve
geta
tion
type
sat
the
sam
plin
gsi
tes,
(c)
polle
n-de
rive
dbi
omes
atpr
esen
tba
sed
only
onsi
tes
for
whi
chhi
gh-
qual
ity
data
was
avai
labl
e,an
d(d
)po
llen-
and
mac
rofo
ssil-
deri
ved
biom
esat
6000
year
s.F
IG.
3.D
istr
ibut
ion
of(a
)po
llen-
deri
ved
biom
esat
pres
ent,
(b)
pres
ent
vege
tati
onty
pes
atth
esa
mpl
ing
site
s,(c
)po
llen-
deri
ved
biom
esat
pres
ent
base
don
lyon
site
sfo
rw
hich
high
-qu
alit
yda
taw
asav
aila
ble,
and
(d)
polle
n-an
dm
acro
foss
il-de
rive
dbi
omes
at60
00ye
ars.
FIG
.3.
Dis
trib
utio
nof
(a)
polle
n-de
rive
dbi
omes
atpr
esen
t,(b
)pr
esen
tve
geta
tion
type
sat
the
sam
plin
gsi
tes,
(c)
polle
n-de
rive
dbi
omes
atpr
esen
tba
sed
only
onsi
tes
for
whi
chhi
gh-
qual
ity
data
was
avai
labl
e,an
d(d
)po
llen-
and
mac
rofo
ssil-
deri
ved
biom
esat
6000
year
s.F
IG.
3.D
istr
ibut
ion
of(a
)po
llen-
deri
ved
biom
esat
pres
ent,
(b)
pres
ent
vege
tati
onty
pes
atth
esa
mpl
ing
site
s,(c
)po
llen-
deri
ved
biom
esat
pres
ent
base
don
lyon
site
sfo
rw
hich
high
-qu
alit
yda
taw
asav
aila
ble,
and
(d)
polle
n-an
dm
acro
foss
il-de
rive
dbi
omes
at60
00ye
ars.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1048 Pavel E. Tarasov et al.
derived from lakes or mires whose pollen source area is northern limit of cool mixed forests was also shiftedcorrespondingly northwards.regional rather than local.
2. Among the forest biomes, temperate deciduous and cool 2. Taiga was apparently reduced in overall area at 6000years, mainly because cool conifer forests extendedconifer forests are well reconstructed. Cool mixed forests
are sometimes shown in the place of temperate deciduous northwards far into what is now the broad taiga belt ofEuropean Russia. Cool conifer forests also occurredforests because of the presence of Picea pollen in the
spectra, partly due to widespread planting. The same further north and east than present in the Ural Mountainsand western Siberia. Cold mixed forest was presentproblem was mentioned by Prentice et al. (1996) as a
weakness of the biomization method when applied to instead of taiga in the extreme north-west of the region(northern Karelia and Kola). However, taiga hadsurface samples in Europe.
3. Cold mixed forest was incorrectly reconstructed in a few attained its modern range in the continental interior(central and southern Siberia and northern Mongolia).places, especially pollen samples subject to long-distance
pollen transport (e.g. from the Caucasus to the One site in western Mongolia shows taiga where thereis steppe today, and taiga was present at some sites inKarakumy desert over the Caspian Sea).
4. The absence of key taxa led to reconstruction of taiga central Yakutia where now there is cold deciduous forest.3. The northern forest limit was extended poleward at 6000in place of cool conifer forest at some locations along
the southern limit of the taiga belt. years. This is shown most clearly by tree macrofossildata from sites in the Yamal and Taymyr peninsulas,5. The map (Fig. 3a) and Tables 5 and 6 show that the
method has a limitation for pollen samples collected in several hundred km north of the modern forest limit,and by increased Picea pollen percentages along theareas with sparse or no vegetation (e.g. the central part
of the hot sandy desert, or the polar desert of the Arctic Arctic coast from the White Sea to Taymyr. The limiteddata available from eastern Siberia, however, indicateislands). When the pollen production of local plants is
extremely low, long distance transport (mostly from that tundra was present at 6000 years in coastal locations,just as it is today.forested areas) dominates, leading to incorrect biome
assignments. This is not likely to cause problems in 4. Apart from the slight encroachment of temperatedeciduous forest in the west, the steppe biome is shownreconstructing vegetation from fossil pollen spectra,
however, because nonvegetated environments do not occupying essentially the same area at 6000 years astoday. There is not enough data to locate the boundarygenerally provide conditions for continuous
sedimentation. between steppe and desert. The available data however,show that arid conditions similar to present were foundnorth of the Aral Sea and in western Mongolia.
Biome reconstructions for 6000 yearsDISCUSSION
Figure 3 confirms the impression from the pollen abundanceOur results for 6000 years are in good agreement withmaps (Fig. 2) that the biome distribution at 6000 yearsprevious studies of Holocene vegetation changes of northern(Fig. 3d) differed substantially from both the actual modernEurasia (e.g. Khotinskii, 1984).biome distribution (Fig. 3b) and the biome distribution as
The extension of temperate deciduous forests at 6000reconstructed from surface samples (Fig. 3c). The 6000years north of their present position, as far as the easternyear biome distributions look even more coherent than theBaltic, implies both warmer summers (or at least a longerpatterns seen in surface pollen data, because the 6000 yeargrowing season), and warmer winters, than today. Thedata are more homogeneous (the fossil pollen data beingoccurrence of temperate deciduous forests at scattered sitesall from peat and lake sediments), and because humanacross the south-eastern Baltic region may imply conditionsimpact on the mid-Holocene vegetation was minimal. Thedrier than present, analogous to the modern forest-steppeavailable 6000 year pollen sites from the Arctic are ratherborder region.sparse; however, the inclusion of tree macrofossil records
Warmer summers during the mid-Holocene haveincreases confidence in the reconstructed tree-line changespreviously been inferred from many pollen sites acrossbecause the macrofossils are not subject to long-distancethe northern and central part of the East-European Plaintransport beyond the forest limit.(Klimanov, 1978, 1987, 1989; Bezusko & Klimanov, 1987;The main features revealed by comparison of Fig. 3(d)Bezusko et al., 1988; Bolikhovskaya et al., 1988; Elovichevawith Fig. 3(b) and (c).et al., 1988). The largest inferred July temperature increase(3–4 °C above the modern value) was reconstructed for the1. At 6000 years the temperate deciduous forest belt
extended both northward and southward from its modern high latitudes north of 60°N; the increase declines almostto zero south of 50°N (Klimanov, 1978). According toposition. The southward extension occurred along the
river valleys as far as the northern Black Sea in the area constrained analogue climate reconstructions for Europe at6000 years (Cheddadi et al., 1997), winter temperatures werecurrently dominated by steppe. The northward extension
was less pronounced. However, individual 6000 year also significantly (up to 2–3 °C) warmer than present in thenorthern part of the Russian Plain. Summer warming insamples record temperate deciduous forest close to the
Gulf of Finland and Lake Ladoga, near the modern mid-to high latitudes at 6000 years is expected as a directeffect of higher-than-present summer insolation caused byboundary between taiga and cool conifer forests. The
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
Biomes from the FSU and Mongolia 1049
changes in the Earth’s orbital geometry (Berger & Loutre, Andreev & Klimanov, 1991). The presence of boreal1991). The summer insolation anomalies were greater in the evergreen conifers in the area that is now dominated byhigh latitudes (where total annual insolation was also higher cold deciduous forests indicates that mid-Holocene wintersthan present), but other (indirect) mechanisms are required were warmer than present also in this region. Pollen-basedto explain winter temperatures higher than present. reconstructions for central Yakutia in fact suggest both that
Conditions drier than present in the band south and July and January temperatures were 2 °C higher, and thatsouth-east of the Baltic Sea were previously reconstructed precipitation was slightly higher, than today during mid-from lake-status data (Harrison et al., 1996). Such Holocene time (Andreev et al., 1989).conditions may reflect an increased incidence of blocking The pollen record provides no evidence that steppeanticyclones centred on the Baltic. (Harrison et al., 1996) occupied a larger area at 6000 years than now (Khotinskii,By contrast, the annual water balance (precipitation minus 1984). Lake-status data from Kazakhstan and Mongoliaevapotranspiration) reconstructed from pollen and lake- (Harrison et al., 1996) even indicate slightly wetterlevel data was 50–150 mm greater than present across most conditions than present during the mid-Holocene, andof the rest of the European part of the FSU (Cheddadi suggest that the direct drying effect of higher 6000 yearset al., 1997). The southward shift of temperate deciduous summer insolation on evapotranspiration was compensatedtrees to the northern coast of the Black Sea, indicates by atmospheric circulation-induced changes inconditions clearly wetter than present. Pollen records from precipitation. However, small forest patches with borealthe southern East-European Plain suggest that patchy and eurythermic conifers that grow today in the Asianforests dominated by broad-leaved deciduous species and steppe were apparently less widely distributed inPinus were common in the valleys of the Dniper, Don, Kazakhstan and Mongolia at 6000 years. This changeDnestr (Khotinskii, 1984; Kremenetskii, 1991) and Volga could indicate that conditions in the interior were drier(Bolikhovskaya, 1990). However, the adjacent plains were at 6000 years than today. Tarasov et al. (1997) analysingcovered by steppe and meadow-steppe vegetation as they the well-dated pollen record from Ozerki (Tarasov, 1992;are today. According to pollen-based climate Kremenetskii et al., 1994), eastern Kazakhstan, concludedreconstructions, the mean July temperature in the lowland that either warmer (and drier) summers or colder wintersnorth of the Black Sea was similar to present while the could explain the absence of conifers during the early toannual precipitation was 50–100 mm higher (Kremenetskii, mid-Holocene. At the same time boreal summergreen taxa1991). (e.g. Betula, Salix) grew continuously at Ozerki. Evergreen
The northward extension of forests in northern Russia at conifers have similar moisture requirements to boreal6000 years implies warmer summers and/or longer growing summergreen trees, but cannot tolerate an absoluteseasons than present. The warming was most pronounced
minimum temperature below −60 °C (Prentice et al.,in European Russia, where tundra was probably absent
1992). Given that at 6000 years winter insolation wasat 6000 years (Khotinskii, 1984) and open boreal forests
9.6% less than at present at 50°N (Berger & Loutre,dominated by spruce and birch extended northwards to the1991) and that the absolute minimum temperature recordedBarents Sea (Bolikhovskaya et al., 1988). In western Siberiatoday in Kazakhstan is −52 °C (Klimaticheskii Atlasthe taiga and cold deciduous forests extended 100–150 kmSSSR, 1960), it is possible that colder than present wintersinto the modern tundra area (Khotinskii, 1984) or up tocould have been a limiting factor for the evergreen conifers500 km further north on the Yamal and Taymyr peninsulasin the cold continental climate of central Asia. Cold(Nikol’skaya & Cherkasova, 1982; Nikol’skaya, 1982;winters at 6000 years are to be expected in low to mid-Vasil’chuk et al., 1983; Volkova et al., 1989; MacDonaldlatitudes, which experienced the largest negative insolationet al. submitted). However, forest vegetation in the far northanomalies, in contrast with high latitudes where wintermay have been represented by individual trees or smalltemperatures are more strongly controlled by atmosphericforest patches (forest tundra), rather than continuous zonalcirculation patterns.taiga or cold deciduous forests. On the Yamal Peninsula,
In conclusion, the results of biomization show a strong,pollen-based temperatures reconstructions for 5750 years coherent spatial pattern to the way that the 6000 year(Nikol’skaya et al., 1989) were 2–3 °C greater in July andvegetation differed from today. These changes can be2 °C greater in January than today, and annual precipitationbroadly explained by orbitally induced changes in insolation,was 100 mm more than present.and can be further used for comparisons with climate modelQualitatively similar changes have been reconstructedsimulations. We have been able to obtain a good datafurther east near the Laptev Sea coast (Nikol’skaya et al.,coverage for much of the FSU and Mongolia, but some1989). However, the mid-Holocene climate change thereregions are still poorly represented. For example, more datawas not strong enough for a northward shift of the forestare needed for the high Arctic and for the southern forestto be detectable in the biome map. Khotinskii (1984)limit, in order to determine more exactly the boundariessuggested that the northward extension of forest in thisamong forest, tundra and steppe at 6000 years. More dataregion at 6000 years was less than 100 km, suggesting aare also needed to reconstruct vegetation changes in themore modest temperature increase than occurred furthermountain regions, since the available data do not providewest.clear evidence for shifts in the elevation and in theA greater extension of Picea at 6000 years compared tocomposition of mountain forests, although such shifts arepresent was noted from pollen records in central and
southern Yakutia (Khotinskii, 1977; Andreev et al., 1989; likely to have occurred.
Blackwell Science Ltd 1998, Journal of Biogeography, 25, 1029–1053
1050 Pavel E. Tarasov et al.
Berdovskaya, G.N. (1982) K paleogeografii ozera Chany.ACKNOWLEDGMENTSPul’siruyushchee ozero Chany, pp. 33–40. Nauka, Leningrad.
The EU-sponsored INTAS project and the NSF Earth Berger, A. & Loutre, M.F. (1991) Insolation values for the last 10System History Program supported the new compilation of million years. Quat. Sci. Rev. 10, 297–317.
Bezusko, L.G. (1973) Concerning the problem of development ofpollen data from the FSU. A substantial part of the newvegetation in the Left-Bank Forest-Steppe of the Ukraine inpollen data for 6000 years was provided during theHolocene from data of spore-pollen investigations. UkrainskiiWorkshop on Late Quaternary Palaeoenvironments ofBot. Zhurnal, 30, 228–237.Northern Eurasia that was held in Horby in August 1996.
Bezusko, L.G. & Klimanov, V.A. (1987) Climate and vegetation ofFunding for this workshop came from the NSF Earththe plain part of the Ukrainian SSR West in the Late-Post-
Systems History Program to the TEMPO (Testing Earth- Glacial Period. Ukrainskii Bot. Zhurnal 43, 54–58.System Models with Palaeoenvironmental Data) Project, Bezusko, L.G., Klimanov, V.A. & Shelyag-Sosenko, Yu.R. (1988)the International Geosphere-Biosphere Programme’s Data Klimaticheskie usloviya Ukrainy v pozdnelednikovye i golotsene.and Information System (IGBP-DIS), the Swedish Institute, Paleoklimaty golotsena evropeiskoi territorii SSSR (ed. by N.A.the Royal Swedish Academy of Sciences (KVA) and the Khotinskii and V.A. Klimanov), pp. 125–135. AN SSSR, Institut
Geografii, Moscow.Swedish Museum of Natural History. Pavel TarasovBlyakharchuk, T.A. (1990) Istoriya rastitel’nosti yugo-vostokacompleted the paper while he was a guest-scientist in
Zapadnoi Sibiri v golotsene (po dannym botanicheskogo i sporovo-Dynamic Palaeoclimatology, Lund University funded bypyl’tsevogo analizov torfa). Unpublished Cand. Sci. Dissertation.KVA. This study is a contribution to BIOME 6000, a globalInstitute of Biology and Biophysics, Tomsk State University,palaeovegetation mapping project sponsored by the IGBP.Tomsk.
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