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Russia's Forests Dominating Forest Types and Their Canopy Density

  • January 2004
Authors:
Alexey Yaroshenko at Greenpeace Russia
Alexey Yaroshenko
  • Greenpeace Russia
Sergey A. Bartalev at Space Research Institute
Sergey A. Bartalev
Dmitry Ershov at Russian Academy of Sciences
Dmitry Ershov
Isaev A.S.
Isaev A.S.
Isaev A.S.
  • This person is not on ResearchGate, or hasn't claimed this research yet.
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Abstract

Map of Russian forests
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Chita
Yakutsk
Vladivostok
Khabarovsk
Birobidzhan
Blagoveshchensk
Yuzhno-Sakhalinsk
Magadan
Petropavlovsk-
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Anadyr
Rostov-on-Don
Krasnodar
Stavropol
Naltchik
Makhatchkala
Elista
40°
50°
40°
50°
60°
20° 30° 40° 50° 60° 70° 80° 100° 120° 140° 150° 160° 180° 170 °
JAPAN
CHINA
MONGOLIA
KAZAKHSTAN
GEORGIA
AZERBAIJAN
UKRAINE
BELORUS
POLAND
LITHUANIA
LATVIA
ESTONIA
FINLAND
SWEDEN
Scale 1:14 000 000
Azimuthal projection
Baykal Lake
Astrakhan
Closed canopy
forests
40-100%
L E G E N D
Open canopy
forests
10-39%
Percent Tree Cover
This work was supported by the John D. and Catharine T. MacArthur Foundation
Space Research Institute of the Russian Academy
of Sciences (RAN)
Forest Ecology and Production Center of the
Russian Academy of Sciences (RAN)
Global Forest Watch Greenpeace Russia
Spruce and Fir Forest
Spruce and Fir Forest
Spruce, fir and Siberian pine dominate, often with presence of birch, aspen,
pine and larch. Other broadleaved deciduous species and Korean pine are
present along the southern border of European Russia and in the south of
the Russian Far East.
Pine Forest
Scotch pine dominates, usually with presence of spruce, birch and aspen
and/or larch at the northeastern edge.
Larch Forest
Larch of different species dominates, often with presence of birch and
aspen. Other species (pine, spruce, Siberian pine) may be mixed along the
southern and western borders of Russia. In the mountains of the Russian
Far East larch species often have undergrowth of Siberian pine.
Broadleaved Deciduous Forest
Broadleaved deciduous species dominate (oak, lime, ash, maple, elm and in
southern European Russia also beech, chestnut and hornbeam). In
mountainous areas (Caucasus, Southern Ural, Sikhote-Alin) with
significant presence of conifers such as spruce, fir and Korean pine.
Stone Birch Forest
Stone birch dominates, often with presence of larch trees or patches of
trees. In Kamchatka this forest has undergrowth of mountain pine, and in
the mountains of Primorye and Sakhalin with presence of spruce and fir.
Dwarf Pine Forest
Dwarf pine dominates in patches or shrubby forest, often with a sparse
upper storey of larch or stone birch.
Birch-Aspen and Mixed Forest
Birch, aspen and gray alder dominate, with presence of coniferous trees or
patches of trees. In most cases, this forest follows logging, clearing or
forest fires.
Areas of Potential Forest
Agricultural and other non-forest ecosystems in which climate and soils
are suitable for forest growth.
Pine Forest Larch Forest
Stone Birch Forest Dwarf Pine Forest Birch-Aspen Forest
Broadleaved Deciduous Forest
Areas of Potential Forest
Russia's Forests
Dominating Forest Types and Their Canopy Density
References
1. Bartalev S.A., Belward A.S., Erchov D.V., Isaev A.S. A New SPOT4-VEGETATION Derived
Land Cover Map of Northern Eurasia. - International Journal of Remote Sensing. - 2003. -
Vol.24. - No.9 - P. 1977-1982
2. Hansen M.C., DeFries R.S., Townshend J.R.G., Carroll M., Dimiceli C., Sohlberg R. A.
Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS
Vegetation Continuous Fields Algorithm (http://modis.umiacs.umd.edu/productvcf.htm).
3. The Forests of the USSR: Map Scale 1:2500000, prepared by the department of the forest
cartography of Souzgiprosleskhoza. M.G. Garsia, ed. Moscow: GUGK, 1990.
4. Vegetation of the USSR (for higher educational institutions): Map Scale 1:4000000.
T.I. Isachenko, ed. Minsk: GUGK, 1990.
5. Digital chart of the world. Environmental Science Research Institute, 1999.
Bartalev S.A., Ershov D.V., Isaev A.S.,
Potapov P.V., Turubanova S.A., Yaroshenko A.Yu.
Russia's Forests
Dominating Forest Types and Their Canopy Density
Scale 1 : 14 000 000
Moscow, 2004
Forests are defined as areas with at least 10% tree
cover, according to the Global Percent Tree Cover
map (Reference 2). Areas with 10% to 39% are con-
sidered open canopy forests, while closed canopy for-
ests have greater than 40% tree cover. Dominating
species and species groups are shown according to
the map of the forests of the USSR (Reference 3),
published in 1990, except for those places where a
comparison with the land cover map of Northern
Eurasia (Reference 1), published in 2003, indicates
that the species composition has changed. Areas
where deciduous or mixed forest has replaced coni--
ferous forest are categorized as "birch-aspen and
mixed forest." Areas with other types of species
change (rare in comparison with the previous case)
are classified based on expert interpretation of the
two compared maps (References 1 and 3).
Potential forest areas, consisting mainly of agricultu-
ral and other non-forest managed ecosystems, are
shown according to the map "Vegetation of the
USSR" (Reference 4). Boundaries of this category are
uncertain and determined based on expert opinion.
The map is intended for educational use.
Latin names of trees, that are mentioned in legend:
ash - Fraxinus sp.; aspen - Populus tremula; beech - Fagus
sp.; birch - Betula sp.; stone birch - Betula ermanii;
chestnut - Castanea sativa; elm - Ulmus sp.; fir - Abies sp.;
gray alder - Alnus incana; hornbeam - Carpinus betulus;
larch - Larix sp.; lime - Tilia sp.; maple - Acer sp.; oak -
Quercus sp.; pine - Pinus sp.; Siberian pine - P. sibirica;
Korean pine - P. koraiensis; Scots pine - P. sylvestris; dwarf
pine - P. pumila; spruce - Picea sp.
Photos: Dahno T.V., Kantor V.A., Kiritchok E.I.,
Piskareva S.B., Potapov P.V.
... More accurate approaches for image classification are also available in [26,27]. However, it seems to be inapplicable for studying the current issue, both due to the lack of high-resolution remote sensing data on the territory of interest and due to the limited accuracy of the available data on fire polygons (1000 m) [28] and vegetation maps (250-500 m) [8,29]. ...
... Current estimates suggest that up to 30% of burned forests of the region are killed by high-severity fire [16], which, however, does not take into account the variability associated with the resistance of certain forest-forming species to fires such as pine (Pinus sylvestris) [4,31,32]. Hence, the classification of fire impact needs to be quantified in relation to dominant tree stands and combinations of vegetation cover in boreal forests of eastern Siberia [8,29]. In this research, we discuss results on the classification of burned areas in 2021 in terms of low, moderate, and high degrees of fire impact on vegetation in relation to the dominant forest stands, close tree stands, and sparse stands and tundra of eastern Siberia. ...
... as pine (Pinus sylvestris) [4,31,32]. Hence, the classification of fire impact needs to b tified in relation to dominant tree stands and combinations of vegetation cover i forests of eastern Siberia [8,29]. ...
Classification of Fire Damage to Boreal Forests of Siberia in 2021 Based on the dNBR Index
Article
Full-text available
  • Jan 2022
Wildfire in Siberia is extensive, affecting up to 15 Mha annually. The proportion of the vegetation affected by severe fires is yet unknown, and it is a problem that requires a solution because post-fire mortality of tree stands in Siberian taiga has a strong effect on the global budget of carbon. The impact of fire in our area of interest in eastern Siberia was analyzed using the normalized burn ratio (NBR) and its pre- versus post-fire difference (dNBR) applied to Landsat-8 (OLI) collected in 2020–2021. In this paper, we present the classification of fire impact in relation to dominant tree stands and vegetation types in boreal forests of eastern Siberia. The dNBR of post-fire plots ranged widely (0.30–0.60) in homogeneous larch (Larix sibirica, L. gmelinii) forests, pine (Pinus sylvestris) forests, dark coniferous stands (Pinus sibirica, Abies sibirica, Picea obovata), sparse larch stands, and Siberian dwarf pine (Pinus pumila) stands. We quantified the proportions of low, moderate, and high fire severity (37%, 39%, and 24% of the total area burned, respectively) in dense tree stands, which were varied to 30%, 57%, and 13%, respectively, for sparse stands and tundra vegetation dominated in the north of eastern Siberia. The proportion of severe fires varied according to the transition from dominant larch stands (33.2% of the area burned) to pine (12.6%) and dark coniferous (up to 26.4%). The current proportion of stand-replacement fires in eastern Siberia is 12–33%, depending on vegetation type and tree density, which is about 2500 thousand hectares in 2021 in the region. According to our findings, the “healthy/unburned vegetation” class was quantified as well at least 700 thousand hectares in 2021.
... Openness of the area to Arctic and Atlantic air masses; interaction of the arctic, polar and tropical air masses; and considerable atmospheric motion both in summer and in winter (especially in the northern and the middle latitudes) define the climate patterns and create a highly variable weather (Lydolph 1977;Myachkova 1983). Due to the moderating influence of the Atlantic Ocean, most of the Russian Plain and surrounding areas experiences a temperate continental climate; only its northernmost part (north of 66°N, Tundra zone) has a subarctic climate (Alisov 1969). ...
... Within the temperate continental climatic area, we distinguish the following four climatic regions (Alisov 1969;Myachkova 1983): ...
... Within the forest zone, the temperature also varies from −4°C in the north-east to +6°C in the south-west. We should note that we present climatic parameters according to the Reference Book on Climate of the USSR (Spravochnik po klimatu SSSR 1964SSSR -1969, where the average temperatures are calculated for the period from 1881 to 1960 and the average precipitation values are calculated for the period from 1891 to 1960 with all corrections on the measurement procedures (details on precipitation measurement and correction are described by Groisman et al. 1991). A short description of climatic changes after 1960 in European Russia can be found at the end of this section. ...
Natural Conditions and General Descriptions of Forest Vegetation and Forest Soils
Chapter
Full-text available
  • Jan 2017
This chapter contains descriptions of topography and hydrography of the Russian Plain and surrounding areas including Eastern Karelia, the Kola Peninsula and the Northern, the Central and the Southern Russian provinces together with the western slope of the Ural Mountains. The main climatic parameters distributed over the study area and average changes in climate during the last century are also discussed. Forest vegetation and forest soils are surveyed for the boreal, the hemiboreal and the nemoral forest regions.
... Figure 1 shows the dominant land cover type and tree species over the entire domain. 139 (Bartalev et al., 2004 (Randerson et al., 2017). The 'small fires' version of GFED4 has a correction 154 applied to address the known bias in BA products to underrepresent the extent and frequency of 155 smaller and/or low intensity fires (Randerson et al., 2012). ...
Climate change, fire return intervals and the growing risk of permanent forest loss in boreal Eurasia
Preprint
  • Nov 2021
Climate change has driven an increase in the frequency and severity of fires in Eurasian boreal forests. A growing number of field studies have linked the change in fire regime to post-fire recruitment failure and permanent forest loss. In this study we used four burnt area and two forest loss datasets to calculate the landscape-scale fire return interval (FRI) and associated risk of permanent forest loss. We then used machine learning to predict how the FRI will change under a high emissions scenario (SSP3-7.0) by the end of the century. We found that there is currently 133 000 km2 at high, or extreme, risk of fire-induced forest loss, with a further 3 M km2 at risk by the end of the century. This has the potential to degrade or destroy some of the largest remaining intact forests in the world, negatively impact the health and economic wellbeing of people living in the region, as well as accelerate global climate change.
... As a result of these events, presently (1) light-demanding species gradually disappear from forests without grazing, because cattle and wild gregarious ungulates maintaining these species are mainly absent now, and (2) the abandoned lands have become overgrown by pioneer trees in stands of different densities depending on the frequency of spring grass fires which are common in populated areas (Bobrovsky and Khanina 2015). On the whole, the proportion of lands covered by forests increased by the beginning of the twenty-first century in central European Russia (Lyuri et al. 2010;Prishchepov et al. 2013), but pioneer trees dominate 77% of all the forested lands (Bartalev et al. 2004). ...
Development of the European Russian Forests in the Holocene
Chapter
Full-text available
  • Jan 2017
The history of forest landscapes in European Russia since the time of the Late Pleistocene is shortly reviewed. Human activities are considered a leading factor in the changes of the forest landscape. The main stages of transformation of the European Russian forests in the Holocene are related to the development of the production economy of people. It is shown that anthropogenic impacts caused the segregation of nearly the entire biotic cover of Eastern Europe into several (three) forest regions and two groups of communities, closed forests vs. communities of open and semi-open landscapes, which require human assistance for their maintenance.
... The boreal forest region of European Russia supports more forest than all other regions ( Fig. 1.9): forests occupy 77% of the area (Bartalev et al. 2004). At that, the northern taiga is less disturbed by man than the Middle and the Southern Taiga: there is relatively less logging and there are fewer fires in the northern forests on loam compared to the more southern forests, while forests on light sands and rubbly soil are almost equally disturbed throughout the entire boreal forest region. ...
Boreal Forests
Chapter
Full-text available
  • Jan 2017
Researches of forest vegetation, forest soil, and features of the historical land use in the boreal region showed that most of the boreal forests have developed as a result of repeated forest fires and cuttings during the last millennium. These impacts simplified the structure of boreal forests and led to the wide occurrence of forests dominated by green mosses and dwarf shrubs in the ground layer of the vegetation with a relatively low species diversity and the prevalence of soil with moor and moor-moder humus horizons. At the same time forests dominated by tall herbaceous species in the ground layer and moder-mull humus in the soil have been found in fire refuges which are located in river valleys and on watersheds as well. Tall herb forests dominated by Picea spp. and Abies sibirica (in the east) have developed in areas without fire and clear-cuttings for more than 500 or 600 years, and they are the richest forest type in terms of species and structural diversity of the vegetation, in phytomass values of the ground layer, and in soil fertility. Treefalls with uprooting, pit-and-mound topography, and deadwood at different stages of decay and overgrowing are the main features of these forests. Dark coniferous forests dominated by tall herbs in the ground layer are forests at the latest successional stage that we observed in the boreal forest region of European Russia.
Host phylogeny is the primary determinant of ectomycorrhizal fungal community composition in the permafrost ecosystem of eastern Siberia at a regional scale
Article
Ectomycorrhizal (EM) fungal communities have been studied worldwide; however, those in the very cold and dry continental climate zone of northern Eurasia remain understudied. We investigated EM fungal community structure on plant roots and its determinants in eastern Siberia. We identified 291 EM fungal taxa belonging to 37 fungal genera from nine sites spanning 2100 km. In a variation partitioning analysis, host plant phylogeny was the primary factor that explained variation in fungal community composition, followed by spatial distance, soil, and climate. Host specificity and preference were attributed to differences in EM fungal community composition among host plants. The EM fungal community on Larix cajanderi, the dominant canopy tree in the region, was characterized by a high proportion of Suillus and Rhizopogon species. This implies that these specialist fungal symbionts have a close ecological relationship with pioneer Larix trees to adapt to the harsh continental climate of Siberia.
Mapping forest areas threatened by fires and windthrows (on the example of the Ural territory)
Article
  • May 2020
The authors discuss the methods and results of mapping the forest susceptibility to wildfires and windthrows on the example of the Ural region. We used the previously published database of fire-and wind-related forest damages in the Ural region for 2000–2016 as input data. The method of mapping is based on the analysis of the relationships of fire- and wind-damaged area with forest species composition, landscape and climatic variables, and with some indicators of anthropogenic development of the territory. The predominant forest species make the main factor determining the exposure to wildfires and windthrows. So, the calculations were performed separately for forests with various predominant species. As a result, the maps of forest susceptibility to wildfires and windthrows were created for the entire territory of the Ural, Perm region and separately for the Krasnovishersk district of the mentioned region. The obtained estimates can be used both in forestry planning and improving the monitoring of wildfires and windthrows.
Long-term dynamics of fire- and wind-related forest losses in northeast European Russia from satellite data
Article
  • Jan 2018
The paper presents a long-term analysis of fire-related and storm-induced forest disturbances in the northeast European Russia for 1985–2016. The forest disturbances are identified with the use of Landsat images, Global Forest Change data (for 2000–2014) and Eastern’Europe Forest Cover Change data (for 1985–2000). We created the database which contains the data on forest disturbances (burned areas and windthrows) with a total area of 572 thousand ha; 82.4 % of them are burned areas, and the remaining 17,6 % include storm-, tornado- and snow-induced forest damage. The comparison of the identified burned areas with official forest fire data for Komi Republic (for 1996–2016) shows their high degree of coincidence. In 1985–2016, more than 5 % of forest-covered areas were damaged by wildfires in the northwestern and central parts of Komi Republic, and also in the northwest of Perm Krai. Storm-induced forest damage was the most significant in the western part of Kirov region, in the northeast of Perm Krai and southeast of Komi republic. It is shown that the fire-related and storm-induced forest damage increases in the last 30 years. However, the linear trends are statistically insignificant. The estimated trends of forest damaged areas differ from previously published estimates for the entire European Russia. These differences may be related to our more detailed analysis of Landsat images for 1985–1999, because we discovered many previously unknown burned areas and windthrows. Also, we estimated the influence of weather condition of summer season on fire-damaged area based on the data of 15 weather stations. The number of days with maximum temperature higher than +25 and +30 °C, and also the hydrothermal coefficient, averaged for June and July, have the strongest correlation with fire-related forest damage. © 2018 Space Research Institute of the Russian Academy of Sciences. All Rights Reserved.
Nemoral Forests
Chapter
Full-text available
  • Jan 2017
Nemoral forests occupy only 19% of the area, which is the lowest proportion of forested lands of all forest regions in European Russia. Most of these forests comprise Quercus robur and Pinus sylvestris plantations of different age along with a prominent part of Betula spp. forests that developed on abandoned agricultural lands and after severe clear-cuttings. The main feature of the nemoral region in European Russia is the existence of rather large tracts of old-growth forests dominated by Quercus robur and shade-tolerant broad-leaved trees, such as Fraxinus excelsior, Tilia cordata, Ulmus glabra, etc., which occur in areas that belonged to the defensive belts of Moscow State in the sixteenth and seventeenth centuries. These forests have experienced diverse anthropogenic impacts, and as a consequence, the structure and composition of their vegetation are different. Forests with a rich composition of shade-tolerant trees, shrubs, and herbaceous species can be found on soils with a thick mull humus horizon. While successional changes in the vegetation lead to the development of nemoral herb forests dominated by shade-tolerant broad-leaved trees, the highest plant diversity demands the sustainable existence of meadows and water-rich habitats. That is possible with the presence of herbivores which physically alter the habitats, such as Bison bonasus and Castor fiber, within the broad-leaved forest landscape. On the whole, due to a favorable climate and the diversity of human impacts, a relatively high level of forest biodiversity is still maintained in the nemoral region in spite of the obvious degradation of the forested lands.
Methods of Investigation
Chapter
Full-text available
  • Jan 2017
This chapter includes a list of the study areas and a map of their localities. The dominant ecological-coenotic approach to the forest vegetation classification together with seven ecological-coenotic groups of plant species and their ecological characteristics are described. The methods of mapping and monitoring the forest cover together with a short review of their applications in European Russia are presented. Field data sampling, data analysis, methods of plant diversity assessment, inventory of the ontogenetic structure of tree populations and the assessment of the successional position of the forest ecosystems are discussed.
A new SPOT4-VEGETATION derived land cover map of Northern Eurasia
Article
Full-text available
  • May 2003
The European Commission's Joint Research Centre and the Russian Academy of Science's Centre for Forest Ecology and Productivity have produced a new 1 km spatial resolution land cover map of Eurasia from 1999 SPOT4-VEGETATION data. The legend is designed to serve users from science programmes, policy makers, environmental convention secretariats, non- governmental organizations, development-aid projects and the national forest service. The 1999 map is also being updated as part of an international exercise to map Global Land Cover for the year 2000. This Letter describes the map legend, the image classification method, the map accuracy assessment process and presents the land cover map.
Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm
Article
Full-text available
The first results of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field algorithm's global percent tree cover are presented. Percent tree cover per 500-m MODIS pixel is estimated using a supervised regression tree algorithm. Data derived from the MODIS visible bands contribute the most to discriminating tree cover. The results show that MODIS data yield greater spatial detail in the characterization of tree cover compared to past efforts using AVHRR data. This finer-scale depiction should allow for using successive tree cover maps in change detection studies at the global scale. Initial validation efforts show a reasonable relationship between the MODIS-estimated tree cover and tree cover from validation sites.
Quercus sp.; pine -Pinus sp.; Siberian pine -P. sibirica; Korean pine -P. koraiensis; Scots pine -P. sylvestris; dwarf pine -P. pumila; spruce -Picea sp
  • Jan 1999
  • S A Bartalev
  • D V Ershov
  • A S Isaev
Digital chart of the world. Environmental Science Research Institute, 1999. Bartalev S.A., Ershov D.V., Isaev A.S., Quercus sp.; pine -Pinus sp.; Siberian pine -P. sibirica; Korean pine -P. koraiensis; Scots pine -P. sylvestris; dwarf pine -P. pumila; spruce -Picea sp. Photos: Dahno T.V., Kantor V.A., Kiritchok E.I., Piskareva S.B., Potapov P.V.