Biogeographical study of West Siberian hemiboreal forest associations with species range overlay methods

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Flora 203 (2008) 234–242 www.elsevier.de/flora

Biogeographical study of West Siberian hemiboreal forest associations with species range overlay methods Matthias H. Hoffmanna, Nikolai B. Ermakovb a Martin-Luther-University Halle-Wittenberg, Institute of Geobotany and Botanical Garden, Am Kirchtor 3, D-06108 Halle, Germany b Laboratory of Ecology and Geobotany, Central Siberian Botanical Garden, Siberian Branch of the Russian Academy of Sciences, 101, Zolotodolinskaya, 630090 Novosibirsk, Russian Federation

Received 15 November 2006; accepted 28 January 2007

Abstract The geographical distributions of plant communities are usually inferred from mapping releve´s. Here, we study another approach to map the ranges of associations and higher syntaxa: the joint distribution of the constant species of the associations, i.e. those species most frequently found in the releve´s. We ask whether the joint distribution of the species reflects the distribution of the associations and higher syntaxa. Because of limited availability of plant distribution maps we consider species occurring in more than 40% of the releve´s of four associations belonging to Western and Central Siberian hemiboreal forests of the class Brachypodio pinnati–Betuletea pendulae. Those species are the most informative for syntaxonomic considerations. The joint distribution is established by overlaying the distribution maps of the species and numerically compared with the mapped distribution of the vegetation communities using Cohen’s Kappa. Most species occurring in the associations have a small to mid-sized range. The range size distribution of the contributing species approaches a normal distribution after logarithmic transformation of the range sizes. The geographical extents of the associations are well reflected by the overlays of all constant species. Removing sequentially the species beginning with those having the smallest distribution ranges from the overlay leads to progressive loss of similarity between mapped and modelled range of the associations. For the higher syntaxa (order and class) the similarity between mapped and modelled range increases first but drops at the end of the removal procedure. The less widespread species are particularly important for the recognition of a local plant community, i.e. the association. In contrast, more widespread species allow the definition of the ranges of higher syntaxa and reveal more large-scale geographic relationships of the vegetation. From our quantitative assessment of mapped and modelled maps of the distribution of plant communities, we conclude that the overlay method is useful to infer the geographical extent of plant communities. r 2008 Elsevier GmbH. All rights reserved. Keywords: Range size; Plant ranges; Synchorology; Syntaxonomy; Eurasian forests

Introduction E-mail addresses: [email protected] (M.H. Hoffmann), [email protected] (N.B. Ermakov). 0367-2530/$ - see front matter r 2008 Elsevier GmbH. All rights reserved. doi:10.1016/j.flora.2007.01.004

The distribution of species and the distribution of plant communities are closely connected. For example, some species are considered to be geographical character

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species, i.e. they are important for the recognition of vegetation units, in analogy to those species that are ecological character species. The analysis of the geographical distribution of associations and higher syntaxa has relied mostly on geographical mapping of releve´s and a subsequent compilation and mapping of higher syntaxa ranges (e.g. Diez-Garretas et al., 2003; Ermakov et al., 2000; Ge´hu and Franck, 1985; Mucina, 1989; Willner, 2002). The reverse approach, i.e. the analysis of the extent of the joint occurrences of species occurring in a vegetation community has less often done. Bridgewater and Cresswell (2003) have mapped vegetation communities based on species records in herbaria and their distribution in bioregions. At the scale of continents or considering the total distribution ranges of species, biogeographical studies have focussed on the description of range types occurring in vegetation units (e.g. Bolognini and Nimis, 1993; Hoffmann et al., 2001; Lausi and Nimis, 1991; Nimis and Bolognini, 1993; Nimis et al., 1994, 1995). The geographical extent of the vegetation unit, the syntaxon range, has not been thoroughly studied (Dierschke, 1994), although Pignatti et al. (1995) suggest that even the highest syntaxonomical unit, the vegetation classes, have a distinct distribution range. Foucault (1981) revealed that towards the range margin of a higher syntaxon, the characteristic species become increasingly rare. Lausi and Nimis (1991) and Dengler (2003) emphasized the joint distribution of species found growing together in vegetation communities. The maps presented by Lausi and Nimis (1991) reflect an area where more than 80% of the species co-occur. Dengler (2003) overlayed the distribution ranges of the diagnostic species for higher syntaxa (mainly classes and orders). Both studies revealed an area with the highest probability to encounter this vegetation community, i.e. that area in which all species co-occur (subsequently for brevity called the core area). However, due to the absence of vegetation data from other regions, where the species should also co-occur, these authors could not test their approach, i.e. assess whether the core area represents indeed the range of the community. The inference that the core area of a joint distribution of species reflects the extent of the syntaxon range is, thus, not yet established. Analysing vegetation pattern using geographical indicators is difficult, because most species are geographical indicators only in sections of their ranges. For example, the European–Siberian species Brachypodium pinnatum, Calamagrostis arundinacea and Serratula coronata indicate only the eastern boundary of the Brachypodio–Betuletea class range in the Baikal region, but they are not geographical indicators in the western part of the class range, e.g. near the Southern Urals. On the other hand, Asian species like Lathyrus humilis, Pleurospermum uralense and Lilium

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pilosiusculum are geographical indicators in the western part of that class range but not in the Baikal region. A spatial analysis of all constant species contributing to a particular vegetation community may thus be helpful. We assess whether distributions of vegetation types may be predicted from overlays of distributions of cooccurring species. A method for the geographical analysis of plants co-occurring in a community is the overlay of their distribution ranges, i.e. the establishment of their joint distribution. This method has produced good results for analyses of diversity patterns (e.g. Korsch, 1999; Preston et al., 2002), range types (e.g. Bolognini and Nimis, 1993; Lausi and Nimis, 1991; Nimis et al., 1994, 1995), geographical patterns of leaf physiognomy (Traiser et al., 2005) and, to some extent, biogeographical classification (e.g. Wohlgemuth, 1996). For larger areas and at the global scale this method has apparently not been used for assessing the distribution of plant communities. The main impediments were probably the scarcity of reliable plant distribution maps and maps of the distribution of plant communities, with which the method can be verified. Here we study four Western and Central Siberian plant communities of hemiboreal forests by means of the ranges of their most constant species. Siberian hemiboreal forests are characterized by the predominance of a few but widespread boreal coniferous and small-leaved deciduous trees. The species rich herb layer consists, in contrast to the tree layer, mostly of temperate species. Hemiboreal forests of Northern Eurasia are an intermediate forest vegetation type between the boreal taiga forests and the temperate broad-leaved forests. These forests occur between the boreal and the forest-steppe zones in a relatively narrow geographical area between 521N and 581N and represent a sub-zone of the boreal forests in Eurasia as well as in North America (Ha¨met-Ahti, 1981). Specifically, we determine the joint distribution areas of the species constantly occurring in these plant communities by overlaying their distribution ranges. We hypothesize that the range overlaps in these overlays are a predictor of distributions of the communities. If this holds true, then the overlay method may be used for predicting the distribution of plant communities, particularly for areas that are not yet thoroughly studied. To assess the effects of species’ range size on prediction of community range, we examined the effects of removal of species from overlays in range-size sequence. If the overlay of the communities’ species may be considered a model of the distribution of the community, what happens if species were removed from the overlay according to their ranges sizes? We also ask whether this sequential removal reveals geographic affinities of the communities?

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Material and methods Synoptic tables of all species and associations of hemiboreal forests and their geographical distribution were obtained from Ermakov et al. (2000) and Ermakov (2003) and are the result of a long-term study of this vegetation type using the Braun–Blanquet approach. These tables contain all species and the constancy values for their occurrence in an association (for constancy see below). In total, the data set comprises 60 associations with 1040 species of higher plant species distributed in Southern Siberia and Northern Mongolia from the Ural mountains east to the Amur river basin. For this study, we focus on four associations of West Siberian hemiboreal forests (the class Brachypodio pinnati–Betuletea pendulae) that were studied in detail for syntaxonomical patterns throughout the whole area. These four associations occur from the Western Siberian lowlands to Lake Baikal, spanning a large longitudinal section of the hemiboreal forests and representing communities of different geographical position within the class. All associations involved in the study represent natural types of the zonal Asian vegetation and are comparatively little influenced by human usage. A short description of the studied associations and their affiliation with higher syntaxa is given in the following section, for further details see Ermakov et al. (2000) and Ermakov (2003). Nomenclature of the species follows Czerepanov (1995). The dominant tree species of the association Peucedano morisoni–Betuletum pendulae Korolyuk ex Ermakov 2002 that is described as small-leaved deciduous grass forests of the forest-steppe zone are Betula pendula and Populus tremula. The herb and shrub layer is comparatively poor and comprises only 36 species. The most characteristic species among others is the name-giving Peucedanum morisonii. This association is placed in the order Calamagrostio epigei–Betuletalia pendulae Korolyuk ex Ermakov 2002 of Western Siberian hemiboreal forests. The association Anemonoido caeruleae–Pinetum sylvestris Ermakov 1991 is dominated in the tree layer by B. pendula and Larix sibirica with a high influence of Pinus sylvestris. Characteristic herbs are, for example Vicia megalotropis, Primula macrocalyx and Aegopodium alpestre. Rather similar is the association Calamagrostio pavlovi–Laricetum sibiricae Ermakov in Ermakov et al. 2000 that has a higher abundance of L. sibirica and P. sylvestris. Pinus sibirica is frequently found in this vegetation type. A characteristic sedge of this forest is Carex amgunensis, but also the grass Calamagrostis pavlovii. The association Festuco ovinae–Pinetum sylvestris Ermakov 1991 is also dominated by P. sylvestris, L. sibirica and B. pendula. Frequently occurring understory species are Pulsatilla patens and Ledum palustre that is in Siberia not confined to wetlands but occurs sometimes in moister forests. The latter three associations belong to

the order Carici macrourae–Pinetalia sylvestris Ermakov, Korolyuk and Lashchinsky 1991, i.e. small-leaved light coniferous grass forests of the Altai, Sayan and Middle Siberian Plateau (Ermakov et al., 1991). A characteristic species shared by these vegetation units is Carex macroura. All associations are included in the class Brachypodio pinnati–Betuletea pendulae Ermakov, Korolyuk and Lashchinsky 1991 of hemiboreal birch forests ranging from Eastern Europe to Central Siberia. The data set for this study comprised 310 species of higher plants having in these associations a constancy value of greater than 40% (constancy classes 3–5, i.e. species occurred in 40–100% of the releve´s). The limitation of the study considering only those constant species instead of all species resulted from the absence of reliable general distribution maps for many of the species. Distribution maps of these species were obtained partly from published atlases (Hulte´n and Fries, 1986; Meusel and Ja¨ger, 1992; Meusel et al., 1965, 1978). Some new distribution data mainly from Siberia and Asia were incorporated to the maps. Many maps had to be newly compiled from the literature according to the method described in Hoffmann and Welk (1999). The geographical locations of the associations were obtained from Ermakov et al. (2000) and Ermakov (2003). Additional information on the distribution of West and Middle Siberian forests types were obtained from Borovikov (1913), Gorodkov (1915), Povarnitsyn (1931), Vasilyev (1931), Golyato (1957), Smirnov (1958), Frolova (1961), Kasnoborov (1961), Popov (1961), Rysin (1962), Kamenetskaya (1969), Lapshina (1963), Peshkova (1964), Vodopyanova (1964), Kamenetskaya et al. (1963), Zhitlukhina and Mirkin (1987), Ilyina et al. (1988), Dymina (1989). The distribution maps and the maps of the associations were digitized and all geographical calculations and manipulations were performed using the program Arc/Info (ESRI, 1992). For the overlay procedures and the calculation of the range sizes the distribution maps were transformed into grids with a cell size of 50  50 km2. Calculations in grids are more easily possible than using the original point and polygon coverages. This cell size of the grids may be appropriate for the sometimes poor resolution of the floristic data. The presence or absence of a species from a grid cell is coded as 1 and 0, respectively. Range sizes of the species’ distribution ranges were estimated by counting the number of occupied grid cells. The overlays of the species ranges were obtained by adding the grids of the species. To assess the similarity between the observed distribution of a vegetation unit of different rank and the modelled (predicted) distribution of this unit as obtained from the overlay of the species distribution ranges Cohen’s Kappa statistic has been applied (e.g. Manel

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et al., 2001; Sim and Wright, 2005). Cohen’s Kappa statistics allows the assessment of the extent in which a model predicts occurrences or similarities better than chance expectation. In contrast to other similarity indices, as for example, the Jaccard or the Dice index, Cohen’s Kappa considers also the joint absence data. Inflation of the number of joint absences may distort the outcome of Kappa calculations. Therefore, the analysis window has to be restricted. Because we used northern hemispheric distribution maps and a vegetation type particularly occurring in Eurasia, we limited the calculation of Cohen’s Kappa to the land surface of Eurasia. Some species of our analysis have a very large range (e.g., Artemisia vulgaris, Vaccinium vitis-idaea) and the restriction to some arbitrary smaller area of Eurasia, for example, to the proximity of the mapped association ranges, may lead to a artificial decrease of false positives and negatives, respectively. Values for the confusion matrix were obtained from the GIS and calculations were performed using the program (SPSS for Windows, 1999). Tests for normality were performed with the Kolmogorov–Smirnov test or the Shapiro– Wilks test for smaller sample sizes for the untransformed and logarithmic-transformed data. 7

The limits of distribution areas of all associations are intrinsically defined by species boundaries. Limiting species, i.e. those species whose range boundaries define the core area of the overlay, may be widespread species having their distribution boundary in that area, or species with a smaller range. For studying the influence of range sizes on the core area, we sequentially removed the species with the large and the small ranges, respectively, and recorded the change of Cohen’s kappa.

Results Range size distribution The range size distribution of the constant species occurring in a particular association is skewed to the right (Fig. 1). Species with very large ranges are not frequently to be observed as constants to a local assemblage of species. Most frequent are species with small to mid-sized distribution ranges. A logarithmic transformation of the range sizes revealed that they depart from normal distribution (Shapiro–Wilks test; Peucedano morisoni–Betuletum pendulae df 38, 25

Peucedano morisoniBetuletum pendulae

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Fig. 1. Range size distribution of the associations’ constant species (constancy categories III–V, i.e. species occurring in 440% of the relevees). Range sizes are given in Mio km2.

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P ¼ 0.045, Anemonoido caeruleae–Pinetum sylvestris df 62, P ¼ 0.002, Calamagrostio pavlovi–Laricetum sibiricae df 47, P ¼ 0.047, Festuco ovinae–Pinetum sylvestris df 39, P ¼ 0.033).

Overlay of species ranges

Ass

Overlaying the constant species of the associations revealed the area of the joint distribution of the species. In the centre of this overlay map appears the area in which all constant species co-occur (the core area) that may be considered to be the model of the associations’ distribution (for examples see Figs. 2 and 3, the picture is for all studied association essentially the same). Around this core area the number of co-occurring constant species decreases in all directions. The core areas reflect the distribution ranges of all four associations widely distributed in Southern Siberia (Figs. 2, 3). The similarity of the core area to the observed range of the association is moderate, i.e. Cohen’s Kappa is mostly between 0.4 and 0.6 (Manel et al., 2001; Sim and Wright, 2005; see Fig. 4, at the very left of the diagrams, i.e. where zero species are removed from the analysis). These values are all significant at the 1% level.

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Fig. 2. Distribution of the association Peucedano morisoni– Betuletum pendulae (black colour) as inferred from the overlay of the constant species. Additionally, the range of the order Calamagrostio epigei–Betuletalia pendulae (dark grey) and the class Brachypodio pinnati–Betuletea pendulae (light grey) are shown (for details see text). The insets show the mapped distribution of the syntaxonomical units.

Ord

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Fig. 3. Distribution of the association Festuco ovinae–Pinetum sylvestris as inferred from the overlay of the constant species. Additionally, the ranges of the order Carici macrourae–Pinetalia sylvestris and the class Brachypodio pinnati– Betuletea pendulae are shown (in this order the grey colour becomes lighter, for details see text). The insets show the mapped distribution of the syntaxonomical units.

Sequentially removing the species with small distribution ranges resulted mostly in a rapid loss of similarity to mapped association ranges. However, Cohen’s Kappa of the associations Anemonoido caeruleae– Pinetum sylvestris and Calamagrostio pavlovi–Laricetum sibiricae (Fig. 4) increased after sequentially removing the species with the smallest ranges. Because species are included in the analysis that occur with a constancy of 440% in the association, they may have their distribution boundary within the range of the vegetation unit. Thus, they occur only in a fraction of the vegetation sample points. Removing Erythronium sibiricum, the species with the smallest range (only 60 grid cells) of the association Calamagrostio pavlovi– Laricetum sibiricae from the analysis, resulted in a considerable increase of Cohen’s Kappa turning from fair-to-moderate similarity of model and observation. The sequential removing of species with the smallest distribution range from the overlay decreases the similarity between the association’s range and the core area rapidly. Conversely, the similarity between the core area and the distribution range of the higher syntaxa (order, class) increases. Cohen’s Kappa achieves moderate values. Having only the species with large

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Peucedano morisoni-Betuletum pendulae 0.6

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Fig. 4. Sequential removing of species with the smallest distribution range from the overlay decreases the similarity between the association’s range and the core area rapidly. Conversely, the similarity between the core area and the distribution range of the higher syntaxa (order, class) increases. At the very left (‘0’) indicates the Cohen’s Kappa values for the overlay including all constant species.

distribution ranges left in the analysis the similarity decreases again. The reverse approach, i.e. removing the species with large ranges first, produced no insight. The similarity of model and real syntaxon starts with the same value as in

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Fig. 4, remains constant over many removals, but drops further or increases in a way that is dependent on the occurrence of the species with a small ranges size. The distribution of the most westerly situated association Peucedano morisoni–Betuletum pendulae (Fig. 2) is reflected by the core area of the associations’ constant species. Removing the 12 species having ranges of less than 7.5 Mio km2 (3000 grid cells) from the overlay revealed a core area that is similar to the range of the order Calamagrostio epigei–Betuletalia pendulae. The core area of an overlay of the 18 species having ranges larger than 12.5 Mio km2 (5000 grid cells) corresponds well to the range of the class Brachypodio–Betuletea. The association Anemonoido caeruleae–Pinetum sylvestris occurs in the north-western sector of the Altai and Western Sayan mountain system. This area is characterized by the occurrence of many thermophilous plant species. The core area of the overlay of the constant species reflects well the distribution range of the association. Some of the constant and less widely distributed species were observed in only a fraction of the observed points. This explains the increase of Cohen’s Kappa during the removing procedure starting with the smallest ranges (Fig. 4). Apparently, many distribution boundaries are to be observed in that area. On the other hand, in spite of the proximity of the distribution boundary of these species they occur with a high constancy in this vegetation unit. The order Carici macrourae–Pinetalia in which the association has been placed, could be modelled by removing species from the overlay with a range of less than 7.5 Mio km2 (3000 grid cells). The core area of this overlay corresponds with the order range. The Brachypodio–Betuletea class resembles the core area of species with a size of larger than 11.25 Mio km2 (4500 grid cells). The range of the association Calamagrostio pavlovi–Laricetum sibiricae is distributed at the upper Jenissej river and well reflected by the core area of all constant species of this vegetation community. E. sibiricum occurs in this association with a constancy of 40–60% (constancy class III) and has its distribution boundary also in the region. Removing of this species from the overlay resulted in an increase of Cohen’s Kappa (Fig. 4). The order Carici macrourae–Pinetalia as well as the class Brachypodio–Betuletea could both best be modelled with the overlay of species with ranges larger than 5 Mio km2 (2000 grid cells). The easternmost association of our analysis, the Festuco ovinae–Pinetum sylvestris (Fig. 3), was described from a small area west of the western Baikal region. The core area of the overlay of all constant species reflects the area of the association. Removing 14 species with distribution ranges of less than 7.5 Mio km2 (3000 grid cells) from the overlay procedure reveals the distribution of the order Carici macrourae–Pinetalia

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with which the association is affiliated. The distribution range of the class Brachypodio–Betuletea may be modelled in a fair quality by an overlay of the species occupying more than 4500 cells (11.25 Mio km2). Comparing the modelled ranges with the mapped ranges of the higher syntaxonomical units (orders and classes) revealed that they are quite similar irrespective of the geographical location of the association and their particular species composition. This pattern resulted not from a particular high number of shared species. For example, the three associations of the order Carici macrourae–Pinetalia sylvestris share only eight species having ranges larger than 5 Mio km2 (2000 cells: B. pendula, Lupinaster pentaphyllus, Galium boreale, L. humilis, Rubus saxatilis, Thalictrum minus, Iris ruthenica, Maianthemum bifolium). Each of the associations comprise between 25 and 34 species having at least this range size, whose overlays produce a comparable area of joint co-occurrence. A similar pattern can be observed for the class ranges that resemble each other across all associations. An exception may be the transitional association Calamagrostio pavlovi–Laricetum sibiricae that mediates to East Asian vegetation. Nevertheless, the western part of the class range of the Brachypodio–Betuletea is reflected in the map.

Discussion The frequency distribution of range sizes among the studied associations revealed that constant species are mostly species of small to mid-sized ranges. This seems to be a common pattern of plant and animal communities (Gaston, 1998). Removal of species from the overlay according to their range sizes showed that associations, at least the geographically restricted ones, are particularly defined in their spatial extent by species having a small range (stenochorous species). In other words, these stenochorous species are characteristic for the geographical recognition of the association, the basic syntaxonomic unit. In contrast, the stenochorous species appear less informative for the higher syntaxonomic units that appear to be characterized by widespread species. If this pattern turns out to be a general pattern, it may guide the selection of geographically characteristic species and the geographical characterization of plant communities. Because the analysis with geographical indicator species is difficult due to their regionally limited explanatory power, a spatial analysis of all constant species of a vegetation community may be helpful. The initial and single criterion for the analysis of the vegetation types with the overlay method was the constancy value of a species in the association. The selection criterion, i.e. the usage of only those species with a constancy value of 40% and higher of occurrences in the associations, was guided by the availability

of distribution maps. Sporadically found plant species are thus excluded and the focus is set to the constant species. Thus, we got a rather high degree of independence from subjective opinions in the analysis. In contrast to previous analyses of the spatial distribution of vegetation types by the overlay method (e.g. Dengler, 2003; Lausi and Nimis, 1991), we were able to assess quantitatively the similarity between mapped and observed distribution using Cohen’s Kappa. The similarity between model and observation promises that the method may indeed be used to infer the spatial extent of vegetation units (Pignatti et al., 1995). Nevertheless, some limitations in the database still exist. Discussing the modelled ranges of associations or the ranges of higher syntaxa, i.e. the core areas of the overlays, it should be kept in mind that the mapped ranges probably underestimate the actual spatial extent due to still incomplete vegetation surveys. Distribution data of plant species were collected over a much longer time period than those for vegetation applying the Braun–Blanquet method. Therefore, the modelled area of associations or those of higher syntaxonomic units may be equal but more probably larger than the mapped occurrences. The different stages of overlays gained a good coincidence between the mapped and the modelled ranges of vegetation units of different syntaxonomical ranks. This rather good coincidence, for e.g. the class range, was obtained although the associations analysed are geographically widely separated and floristically quite different. This result did not rely on some shared widespread species contributing to the association. Best results for higher syntaxonomical ranks, however, were obtained in analyses of associations that are situated rather central in the mapped range of the higher units. For example, the best models for the order and class ranges were received from the analysis of the two associations Peucedano morisoni–Betuletum pendulae and Anemonoido caeruleae–Pinetum sylvestris that are occupying a central geographical position in the Brachypodio–Betuletea class. This observation is similar to that of Foucault (1981), towards the margins of a syntaxon range the characteristic species become increasingly rare. The overlay method may help to solve many questions about syntaxonomical relationships of zonal vegetation types (Pignatti et al., 1995). For example, the Peucedano morisoni–Betuletum pendulae is less species rich compared with the other associations considered in this study. Due to the low number of species and the virtual absence of geographical local character species, the association caused in the past problems with its affiliation to a higher syntaxonomical unit (Ermakov et al., 2000). Due to the overlay, the position of the Peucedano morisoni–Betuletum in the order Calamagrostio epigei–Betuletalia pendulae, i.e. birch and aspen–birch–grass forests of the southern part of the

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West Siberian Lowlands, is strongly supported. Another example of an association whose affiliation with a higher syntaxonomic unit could be confirmed in this study is the Calamagrostio pavlovi–Laricetum sibiricae that occurs at the boundary between South-Siberian hemiboreal forests of the class Brachypodio–Betuletea and Central Asian hemiboreal forests of the class Rhytidio–Laricetea. The overlays revealed that this vegetation type belongs to the more northerly and westerly distributed order Carici macrourae–Pinetalia and the class Brachypodio–Betuletea. However, the influence of Western Eurasian flora declined as compared, for example, with the association Peucedano morisoni–Betuletum pendulae, resulting in an almost conjunction of the order and class models. Geographic relationships of flora and vegetation are revealed by the overlay method. The overlays of the higher syntaxonomic units, i.e. orders and classes, revealed the proximity of the studied hemiboreal forests to European and Western Eurasian vegetation types. Particularly the core ranges that have been used to model the distribution ranges of classes extend frequently into Europe, but predict hardly an occurrence of this vegetation type east of Lake Baikal. The class Brachypodio–Betuletea includes communities, which are dominated by boreal trees (P. sylvestris, L. sibirica, B. pendula, P. tremula) and represents, thus, a southern type of boreal vegetation. On the other hand, characteristic mosses, herbs, semishrubs and shrubs of the true boreal taiga forests of the Vaccinio–Piceetea class do not play an essential role in the Siberian hemiboreal forests. The understory of the hemiboreal forests comprises a total of about 800 species of shrubs and herbs of mainly Western Eurasian temperate flora and vegetation (broad-leaved forests, xerophytic grasslands, meadows, see Ermakov et al., 2000). The figures of the core areas clearly demonstrate the strong plant–geographical relations of the Siberian hemiboreal forests with vegetation types of the nemoral zone rather than with vegetation of the boreal taiga zone.

Acknowledgements We thank H. Bruelheide, E. G. Mahn, and K. Woods for discussions. The work was supported by the Russian Foundation for Basic Sciences (Grant 03-04-49746 and 06-04-48971) and the German Academic Exchange Programme (DAAD, Ostpartnerschaften).

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