We collected the available relative pollen productivity estimates (PPEs) for
27 major pollen taxa from Eurasia and applied them to estimate plant
abundances during the last 40 ka cal BP (calibrated thousand years before
present) using pollen counts from 203 fossil pollen records in northern Asia
(north of 40
High northern latitudes such as northern Asia experience above-average temperature increases in times of past and recent global warming (Serreze et al., 2000; IPCC, 2007), known as polar amplification (Miller et al., 2010). Temperature rise is expected to promote vegetation change as the vegetation composition in these areas is assumed to be controlled mainly by temperature (J. Li et al., 2017; Tian et al., 2018). However, a more complex response can occur mainly because vegetation is not linearly related to temperature change (e.g. due to resilience, stable states, or time-lagged responses; Soja et al., 2007; Herzschuh et al., 2016) and/or vegetation is only indirectly limited by temperature while other temperature-related environmental drivers such as permafrost conditions are more influential (Tchebakova et al., 2005).
Such complex relationships between temperature and vegetation may help
explain several contradictory findings of recent ecological change in
northern Asia. For example, simulations of vegetation change in response to
a warmer and drier climate indicate that steppe should expand in the
present-day forest–steppe ecotone of southern Siberia (Tchebakova et al.,
2009) but, contrarily, pine forest has increased during the past 74 years,
probably because the warming temperature was mediated by improved local
moisture conditions (Shestakova et al., 2017). In another example, evergreen
conifers, which are assumed to be more susceptible to frost damage than
These findings on recent vegetation dynamics that contradict a straightforward vegetation–temperature relationship may be better understood in the context of vegetation change over longer timescales. Synthesizing multi-record pollen data is the most suitable approach to investigate quantitatively the past vegetation change at broad spatial and long temporal scales. Broad spatial scale pollen-based land-cover reconstructions have been made for Europe (e.g. Mazier et al., 2012; Nielsen et al., 2012; Trondman et al., 2015) and temperate China (Li, 2016) for the Holocene. However, vegetation change studies in northern Asia are restricted to biome reconstructions (Tarasov et al., 1998, 2000; Bigelow et al., 2003; Binney et al., 2017; Tian et al., 2018), which do not reflect compositional change. Syntheses of pure pollen percentage data are not appropriate due to differences in pollen productivity, which may result in an overestimation of the strength of vegetation changes (Wang and Herzschuh, 2011). This might be particularly severe when strong pollen producers such as pine (Mazier et al., 2012) invade areas dominated by low pollen producers such as larch (Niemeyer et al., 2015). Marquer et al. (2014, 2017) also demonstrated the strength of pollen-based REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) estimates of plant abundance in studies of Holocene vegetation change and plant diversity indices in Europe. Accordingly, syntheses of quantitative plant cover derived from the application of pollen productivity estimates (PPEs) to multiple pollen records (Trondman et al., 2015; Li, 2016) should be a better way to investigate Late Glacial and Holocene vegetation change in northern Asia.
In this study, we employ the taxonomically harmonized and temporally standardized fossil pollen datasets available from eastern continental Asia (Cao et al., 2013, 2015) and Siberia (Tian et al., 2018) covering the last 40 ka cal BP (henceforth abbreviated to ka). We compile all the available PPEs from Eurasia and use the mean estimate for each taxon. Finally, we quantitatively reconstruct plant cover using the REVEALS model (Sugita, 2007) for 27 major taxa at 18 key time slices. We reveal the nature, strength, and timing of vegetation change in northern Asia and its regional peculiarities, and discuss the driving factors of vegetation change.
The fossil pollen records were obtained from the extended version of the
fossil pollen dataset for eastern continental Asia containing 297 records
(Cao et al., 2013, 2015) and the fossil pollen dataset for Siberia with 171
records (Tian et al., 2018). For the 468 pollen records, pollen names were
harmonized to genus level for arboreal taxa and family level for
herbaceous taxa, and age-depth models were re-established using the Bayesian
age-depth modelling (further details are described in Cao et al., 2013). We
selected 203 pollen records from lacustrine sediments (110 sites) and peat
(93 sites) north of 40
Selected time windows.
We selected 18 key time slices for reconstruction (Table 1) to capture the
general temporal patterns of vegetation change during the last 40 ka, i.e.
40, 25, 21, 18, 14, and 12 ka during the late Pleistocene and 1000-year
resolution (500-year time windows around each millennium, i.e. 0.7–1.2, 1.7–2.2 ka, etc.) during the Holocene. For the 0 ka time slice, the ca.
150-year time window (
Fall speed (FS) of pollen grains and mean relative pollen productivity estimate (PPE) with standard error (SE) for the 27 selected taxa. Plant functional type (PFT) assignment is according to previous biome reconstructions (Tarasov et al., 1998, 2000; Bigelow et al., 2003; Ni et al., 2010).
The REVEALS model assumes the PPEs of pollen taxa are constant variables
over the target period and requires parameter inputs including sediment
basin radius (m), fall speed of pollen grain (FS, m s
We collected available PPEs for the 27 selected pollen taxa from 20 studies
in Eurasia (Table A2). We calculated the mean PPE from all available PPE
values, but excluded records with PPE
The REVEALS model generally performs best with pollen records from large lakes, although multiple pollen records from small lakes and bogs (at least two sites) can also produce reliable results where large lakes are absent (Sugita, 2007; Trondman et al., 2016). Here, due to the sparse distribution of available sites, we divided the 203 sites into 42 site groups, based on criteria of geographic location, vegetation type (vegetation zone map modified from Tseplyayev, 1961; Dulamsuren et al., 2005; Hou, 2001), climate (based on modern precipitation and temperature contours), and permafrost (Brown et al., 1997) following the strategy of Li (2016); the pollen data within one site group should be of similar components and temporal patterns. To ensure the reliability of REVEALS estimates of plant cover, each group includes at least one large lake or two small sites (small lakes or bogs; Fig. 1; Table A3).
Distribution of the 42 site groups together with the modern vegetation zones and permafrost extent in northern Asia. The vegetation-zone map modified from Tseplyayev (1961), Dulamsuren et al. (2005), and Hou (2001) includes the following. A: tundra, B: taiga forest, C: temperate mixed conifer–deciduous broadleaved forest, D: temperate steppe, E: semi-desert and desert; and F: warm-temperate deciduous forest.
The REVEALS model was run with a mean wind speed set to 3 m s
The abundance variations in the seven PFTs during the Holocene (time slices
between 12 and 1 ka) from 36 site groups were used in a clustering analysis.
Six site groups had to be excluded from the analysis due to poor coverage of
time slices (G1, G5, G17, G19, G27, G42). For site groups with
On a glacial–interglacial scale, marked temporal changes in the occurrence
and abundance of PFTs are revealed, in particular the high cover of tree
PFTs during the Holocene as opposed to the widespread open landscape during
the glacial period. In contrast, vegetation changes in northern Asia within
the Holocene are rather minor with only slight changes in PFT abundances.
Cluster analyses of grouped vegetation records from the Holocene find five
clusters (Fig. A3). Their spatial distribution is largely consistent with
the distribution of modern vegetation types as characterized by certain
PFTs. (1) Records from the forest–steppe ecotone (e.g. G12, G21; Fig. 2a) in
north-central China and the Tianshan (the mentioned geographic
locations are indicated in Fig. A4) have high tree PFTs during the middle
Holocene. (2) Areas in southern and south-western Siberia and north-eastern
China were covered by cool-temperate mixed forest or light taiga with a high
diversity of trees throughout the Holocene (e.g. G2, G7, G14, G29; Fig. 2b).
(3) The West Siberian Plain and south-eastern Siberia that are presently
covered by open dark taiga forests (e.g. G8, G9, G33; Fig. 2c) had an even
higher abundance of evergreen conifer trees during the middle Holocene than
at present. (4)
The turnover in PFT composition is
Temporal changes in plant functional type (PFT) cover, as proportions, for the site groups from the warm temperate forest margin zone
Six site groups from the warm temperate forest–steppe transition zone (G6, G21, G22) and from the lowlands adjacent to mountainous forest in arid central Asia (G12, G13, G16) are clustered together (Fig. 3). Our results indicate that these areas, which are now dominated by arid-tolerant shrub and steppe species, had more arboreal species, mainly evergreen conifer tree taxa, in the middle Holocene (Fig. 2a). For example, north-central China (G21) has a marked mid-Holocene maximum in forest cover (7–4 ka; mean 51 %). However, certain peculiarities are noted: open landscape is reconstructed between 14 and 7 ka in northern Kazakhstan (G6), followed by an abundance of evergreen conifer trees and an increase in boreal deciduous trees that maintain high values (mean 30 %) after 7 ka. In the eastern branch of the Tianshan (G12), evergreen conifer trees are highly abundant from 10 to 7 ka and after 2 ka, while low abundance occurs from 14 to 11 ka and from 6 to 3 ka. In the Gobi desert near the Tianshan (G16) there was an even higher abundance of arid-tolerant species with no notable temporal trend in abundance of arboreal species. We assume that the high arboreal cover at site groups G13 and G22 at 14 and 12 ka originates from riverine transport and therefore exclude them from further analyses.
Eight site groups located in (or near) the temperate mixed conifer–deciduous
broadleaved forest zone (G2, G29, G30, G31) and taiga–steppe transition zone
(G7, G14, G15, G18) show similar PFT compositions and temporal evolutions.
At these sites, evergreen conifer tree is the dominant PFT intermixed with
other arboreal PFTs, such as deciduous conifers (
Evergreen conifer tree is the dominant PFT at 40, 25, and 21 ka in the
southern part of north-eastern China (G29),
Clustering results of the 36 site groups represented by the colour of the boxes, with the age of primary vegetation changes (middle row of each box; data in brackets mean the hierarchical clustering failed the broken-stick test) and the compositional change (turnover; lower row) during the Holocene.
Open landscape is revealed for the southern Ural region (G2) with high
abundances of herbaceous species at 14 ka. The cover of
In the taiga–steppe transition zone,
Site groups with dark taiga forest from western Siberia (G3, G4, G8, G9),
the Baikal region (G20), and south-eastern Siberia (G32, G33, G34) form one
cluster sharing similar PFT compositions dominated by evergreen conifer
trees, with
On the West Siberian Plain (G8, G9), high cover of
In the Baikal region (G20), a relatively closed landscape is revealed at 40 ka; openness then increases to
In south-eastern Siberia (G32, G34), arboreal abundance is high in the early
and late Holocene, but low in the middle Holocene. South of Sakhalin Island
(G33), a closed landscape is revealed between 40 and 1 ka with
Plant composition of this cluster is dominated by
Plant compositions of this cluster are characterized by high abundances of
boreal shrubs and tundra forbs.
In north-eastern Siberia, arboreal cover shows a decreasing trend from
southerly site groups (G35, G36, G37; Fig. 2d) to northerly ones (G40, G38,
G39, G41) following the increasing latitude. In the Olsky District, temporal
patterns of vegetation changes in G37 are consistent with G36, with stable
vegetation during the Holocene and increases in evergreen conifer tree
abundance from ca. 9 ka. Arboreal composition on the southern Kamchatka
Peninsula (G35) is dominated by boreal deciduous trees during the first
stage of the Holocene, followed by rising abundances of
In north-eastern Siberia (G40, G38, G39, G41), the landscape is dominated by forb tundra with sparse shrubs between 40 and 21 ka; the cover of shrubs increases at 14 ka and arboreal cover (dominated by boreal deciduous trees) increases in the early Holocene (11 or 10 ka). Shrubs maintain a high abundance throughout the Holocene, while trees peak between 10 and 2 ka generally (Fig. 2e).
The overall patterns of pollen-based REVEALS estimates of land cover are generally consistent with previous vegetation reconstructions. Although only a few site groups cover the period from 40 to 21 ka, a consistent vegetation signal indicates that relatively closed landscapes occurred in south-eastern Siberia, north-eastern China, and the Baikal region (Fig. 2), while most of Siberia was rather open, particularly around 21 ka (Fig. 2). These findings are consistent with previous pollen-based (Tarasov et al., 1998, 2000; Bigelow et al., 2003; Binney et al., 2017; Tian et al., 2018) and model-estimated biome reconstructions (Tian et al., 2018). During the late Pleistocene (40, 25, 21, 14 ka), steppe PFT abundance was high in central Yakutia and north-eastern Siberia (e.g. G25, G36, G37, G39, G40, G41), which may reflect the expansion of tundra–steppe, consistent with results from ancient sediment DNA which reveal abundant forb species during the period between 46 and 12.5 ka on the Taymyr Peninsula (Jørgensen et al., 2012). The tundra–steppe was replaced by light taiga in southern Siberia and by tundra in northern Siberia at the beginning of Holocene or the last deglaciation, which is consistent with ancient DNA results (forbs-dominated steppe-tundra; Willerslev et al., 2014).
During the Holocene, reconstructed land cover for each site group is generally consistent with their modern vegetation. The slight vegetation changes are represented by changes in PFT abundances rather than by changes in PFT presence or absence. Minor changes are also indicated in the cluster analysis, which shows that plant compositions and their temporal patterns are consistent among the site groups within the same modern vegetation zone (Fig. 3). PFT datasets from only 19 site groups pass the broken-stick test for clustering analysis, and most of them have only one significant vegetation change, further supporting the case that only slight changes occurred during the Holocene in northern Asia. In addition, the low total amount of PFT change (turnover) over the Holocene for most site groups supports the view of slight temporal changes in land cover.
Vegetation turnover on the Tibetan Plateau inferred from pollen percentages
is documented to overestimate the strength of vegetation changes (Wang and
Herzschuh, 2011). This matches with our results. In central Yakutia, the
pollen percentage data indicate a strong vegetation change during the middle
Holocene, represented by a sharp increase in
Pollen-based turnover estimates from southern Norway range from 0.84 to 1.3 SD (mean 1.02 SD) for 10 Holocene pollen spectra (Birks, 2007), and from northern Europe from 0.01 (recent) to 0.99 (start of the Holocene) SD for three sites (N Sweden, NW and SE Finland) (Marquer et al., 2014). Moreover, the REVEALS-based turnover estimates (0.3–1) for northern Europe are significantly higher than the pollen-based one (0.2–0.8) from 11 to 5.5 kyr BP. The same is true for all other regions studied by Marquer et al. (2014) in north-western Europe, and the turnover estimates (pollen- and REVEALS-based) are generally higher at lower latitudes from southern Sweden down to Switzerland and eastwards to Britain and Ireland. These European values are higher than our REVEALS-based turnover estimates (from 0.37 to 0.88 SD, mean 0.66 SD; G3, G8, G9, G23, G24, G25, G36, G37) from a similar latitudinal range (Fig. 3). The fewer parameters used in the turnover calculations for northern Asia (PFTs) compared to Europe (pollen taxa) is a potential reason for the lower turnover obtained in this study. In addition, the PPE-based transformation from pollen percentages to plant abundances may reduce the strength of vegetation changes (Wang and Herzschuh, 2011). Aside from the methodological aspects, the lower turnover in northern Asia may, at least partly, originate from differences in the environmental history between northern Europe compared with northern Asia, i.e. glaciation followed by postglacial re-vegetation vs. non-glaciated areas with trees in refugia, respectively, and a maritime climate with temperature-limited vegetation distribution vs. a continental climate with temperature- and moisture-limited vegetation.
We consider the REVEALS-based regional vegetation-cover estimations in this study as generally reliable with reasonable standard errors (Fig. A5) thanks to the thorough selection of records with high-quality pollen data and reliable chronologies. In addition, the landscape reconstructions are generally consistent with previous syntheses of past vegetation change (e.g. Tian et al., 2018) and known global climate trends (Marcott et al., 2013), plus the clustering results of PFT abundance are consistent with modern spatial vegetation patterns. That said, this study faced two major methodological challenges, discussed below, that may reduce the reliability of the obtained quantitative land-cover reconstructions: (1) the low number of PPEs and their origin and (2) restrictions with respect to the number, distribution, and type of available sites.
Twenty PPE sets were used which mostly originate from Europe and temperate
northern China. The available PPEs were estimated from various environmental
and ecological settings, which might cause regional differences in each PPE.
And PPEs of different species within one family or genus were included in
our mean PPE calculation for the family or genus, ignoring the inter-species
differences. Also, some taxa have few available PPEs with significant
differences (such as
In this study, we attempt to reconstruct past landscape changes at a
regional scale. Pollen signals from large lakes are assumed to reflect
regional vegetation patterns (e.g. Sugita et al., 2010; Trondman et al.,
2015). If large lakes are absent in a region, multiple small-sized sites can
be used, although error estimates are usually large (Sugita, 2007; Mazier et
al., 2012; Trondman et al., 2016). In our study, 70 % of the time slices
for the 42 site groups include pollen data from large lakes (i.e. radii
On a glacial–interglacial scale, pollen-based reconstructed land-cover changes in northern Asia are generally consistent with the global climate signal (e.g. sea-surface temperature: Pailler and Bard, 2002; ice-core: Andersen et al., 2004; solar insolation: Laskar et al., 2004; and cave deposits: Cheng et al., 2016; Fig. A6). For example, the relatively high arboreal cover at 40 ka (e.g. G20) corresponds with the warm MIS 3 record from the Baikal region (Swann et al., 2005). The open landscape at 25 and 21 ka (e.g. G25, G36) reflects the cold and dry last glacial maximum (e.g. Swann et al., 2010). Furthermore, the relatively high arboreal cover during the Holocene is consistent with the warm and wet climate (occurring in most site groups). The primary vegetation change in north-eastern China (G29, G30) occurs in the early Holocene (11.5 and 10.5 ka), caused by the rapid increase in abundance of temperate deciduous trees, which may reflect the warmer climate and enhanced summer monsoon known from that region at the beginning of the Holocene (Hong et al., 2009; Liu et al., 2014).
A sensitivity analysis of model-based biome estimation reveals that precipitation plays an important or even dominant role in controlling vegetation changes in arid central Asia (e.g. Tian et al., 2018). The climate of central Asia during the early Holocene is inferred to be quite dry and moisture increase occurs at ca. 8 ka revealed by a series of multi-proxy syntheses (Chen et al., 2008, 2016; Xie et al., 2018) and model-based estimations (Jin et al., 2012). In the taiga–steppe transition zone (south-eastern Siberia and north-central Asia, e.g. G6, G12, G14, G18), a relatively open landscape is reconstructed for the early Holocene and abundances of forest taxa increase after ca. 8 ka, which are consistent with the moisture evolution, and imply the importance of moisture in controlling vegetation changes. Our results support the prediction of an expansion of steppe in the present forest–steppe ecotone of southern Siberia in response to a warmer and drier climate in the future (Tchebakova et al., 2009). During the late Holocene, the decreases in forest cover in the forest–steppe ecotone of north-central China and central Asia are ascribed to the drying or cooling climate, respectively, by sensitivity analysis (Tian et al., 2018). Previous studies argued that the enhanced human impacts might be important factors for the reduction in forest cover (e.g. Ren, 2007); however, our study fails to determine its contribution on vegetation changes.
High abundances of
Our results indicate that climate change is the major factor driving
land-cover change in northern Asia on a long temporal scale. However,
climate change cannot fully explain the changes in arboreal taxa abundance
for the West Siberian Plain (G8, G9) and sandy places in central Yakutia
(G23, G24, G25). In addition to climate, changes in permafrost condition
(Vandenberghe et al., 2014) and fire regime may have played a central role
in vegetation change.
Population changes in herbivores could also be an important factor for vegetation change at a regional scale during certain intervals (Zimov et al., 1995; Guthrie, 2006). As with our pollen-based land-cover reconstruction, a circumpolar ancient DNA meta-barcoding study confirms the replacement of steppe-like tundra by moist tundra with abundant woody plants at the Pleistocene–Holocene transition (Willerslev et al., 2014). According to Zimov et al. (1995, 2012), such a change cannot be explained by climate change alone, and thus a reduced density of herbivores is considered to be a major driving factor of steppe composition reduction, since a reduced number of herbivores is insufficient to maintain the open steppe landscapes and so causes a decrease in steppe area (Zimov et al., 1995; Guthrie, 2006). Our land-cover reconstruction fails to address the contribution of herbivores to vegetation changes, but the extinction of herbivorous megafauna would add to the complexity of the interactions among vegetation, climate, and permafrost.
Regional vegetation based on pollen data has been estimated using the REVEALS model for northern Asia during the last 40 ka cal BP. Relatively closed land cover was replaced by open landscapes in northern Asia during the transition from MIS 3 to the last glacial maximum. Abundances of woody components increase again from the last deglaciation or early Holocene. Pollen-based REVEALS estimates of plant abundances should be a more reliable reflection of the vegetation as pollen may overestimate the turnover, and indicates that the vegetation was quite stable during the Holocene as only slight changes in the abundances of PFTs were recorded rather than mass expansion of new PFTs. From comparisons of our results with other data, we infer that climate change is likely the primary driving factor for vegetation changes on a glacial–interglacial scale. However, the extension of evergreen conifer trees since ca. 8–7 ka throughout Siberia could reflect vegetation–climate disequilibrium at a long-term scale caused by the interaction of climate, vegetation, fire, and permafrost, which could be a palaeo-analogue not only for the recent complex vegetation response to climate changes but also for the vegetation prediction in future.
The used fossil pollen dataset with the
re-established age-depth model for each pollen record have been made
publicly available in PANGAEA (
Distribution of the 203 fossil pollen sites together with the modern permafrost extent in northern Asia. The number of each site is used as its site ID in Table A1.
Slight percentage changes for five major plant taxa reconstructed by the REVEALS model with different bog radii (5, 10, 20, 50, 100, 200, and 500 m).
Cluster diagram of the site groups based on the plant functional type dataset.
Map of the study area showing the geographic locations mentioned in the text.
Selected examples of standard errors for seven plant functional type (PFT) reconstructions at site groups G21, G20, and G36 at 6 ka.
Proxy-based climate reconstructions from the Northern
Hemisphere and insolation variations during the last 40 ka cal BP discussed
in the paper. NGRIP: the North Greenland Ice Core Project (Andersen et al.,
2004); Sanbao cave (Cheng et al., 2016); Alkenone-derived sea-surface
temperatures (SST) from deep-sea cores SU8118 and MD952042 (Pailler and Bard,
2002); solar insolation in July at 60
Metadata for all pollen records used in this study.
For a list of original publications, see
Continued.
Continued.
Continued.
Continued.
LSC: liquid-scintillation counting; A: terrestrial plant macrofossil; B:
non-terrestrial plant macrofossil; C: peat; D: pollen; U: unknown; E: total
organic matter from silt; F: animal remains or shell; G: charcoal; H:
Pollen productivity estimates (PPEs) with their standard
errors (SEs) for 27 pollen taxa from 20 study areas. Estimates where SE
Continued.
Number of pollen records from large lakes (
XC and UH initiated and designed the study; XC and FT performed the land-cover reconstruction; FL and MJG were involved with the methods of the reconstruction; NR and QX contributed pollen data; XC wrote the preliminary version of the article, on which all co-authors commented.
The authors declare that they have no conflict of interest.
This article is part of the special issue “Paleoclimate data synthesis and analysis of associated uncertainty (BG/CP/ESSD inter-journal SI)”. It is not associated with a conference.
The authors would like to express their gratitude to all the palynologists who, either directly or indirectly, contributed their pollen records and PPE results to our study. This research was supported by the German Research Foundation (DFG) and the PalMod project (BMBF). Furong Li and Marie-José Gaillard thank the Faculty of Health and Life Science of Linnaeus University (Kalmar, Sweden), the China-Swedish STINT Exchange Grant 2016–2018, and the Swedish Strategic Research Area on ModElling the Regional and Global Earth system (MERGE) for financial support. This study is a contribution to the Past Global Changes (PAGES) LandCover6k working group project.
This research has been supported by the German Research Foundation (DFG) and the PalMod project (BMBF).The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association.
This paper was edited by Lukas Jonkers and reviewed by two anonymous referees.