Classification of Russia's Forests in Relation to Global Climate Warming

This study involves investigating the sensitivity to temperature of Russia's forest communities. Factors taken into consideration were mean annual temperature; standard deviation and temperature tolerance limits covering forests across the country. A new numerical classification of forests, related to predicted global climate warming (GCW) has been developed based on cluster analyses. New temperature-forest associations have been interpreted in order to develop a framework for the adaptation strategy to a predicted GCW. Quantitative parameters of the classification allow for the assessment of the magnitude, spatial and temporal dynamics of the GCW affect on forests. As a result, it is suggested that developed classification in forest inventory and management systems should be introduced in Russia

A New Digital Georeferenced Database of Soil Degradation in Russia

Information on human-induced soil degradation in Russia has now been compiled in a new georeferenced database. It comprises the latast data on the status of soil degradation in Russia, including soil deterioration in non-agricultural regions. The information has been linked to a digital soil database, which has recently been prepared for the FAO by the Dukachaev Soil Institute. Soil degradation attributes were derived from unpublished maps compiled for the State Committee for Land Resources and Land-Use Planning of Russia. The Analysis shows that more than 14.5% (243 million ha) of the Russian territory is affected by soil degradation caused by a variety of reasons, including socio-economic changes, and improper management and technology. The assessment reveals that the rate of soil degradation and loss of soil productivity in Russia has been fairly rapid

Forest and Temperature Associations of Russia Relating to Global Climate Warming

We have developed forest and temperature associations for Russia that relate forest communities of Russia with mean annual temperature, standard deviation of mean annual temperature, and temperature tolerance limits. These associations are derived from analysis of the frequency of forest occurrence in different temperature regimes, and were interpreted in order to develop a framework for adaptation strategies for Global Climate Warming (GCW)

Soils of Russia: Correlated with the Revised Legend of the FAO Soil Map of the World and World Reference Base for Soil Resources

The Soil Map of the Russian Soviet Federative Socialist Republic (SMR; Fridlund, 1998) at scale 1:2.5 was compiled through the joint effort of many pedologists around the country. Practically all pedological centers and institutes in Russia contributed their expertise and scientific knowledge accumulated during more than two decades to the map. The map legend comprises the latest soil-genetic classification concepts in which the soil characteristics have been considered together with soil-forming factors. The soil-geographical background of the map introduces a variety of geographical regularities of soil spatial distributions among which the soil zonality and the soil cover structure have been comprehensively represented. Although the SMR is regarded as the major inventory document at the country scale, it is not widely known. The complexity of the legend and specific soil nomenclature have been the main factors confounding implementation of the map. To make the SMR accessible, the correlation of the Soil Map of the World (SMW; FAO, 1998) and the World Reference Base for Soil Resources(WRB; FAO, 1998) was made as transparent as possible

Soils of Russia - Correlated with the Revised Legend of the FAO Soil Map of the World

The "Soil Map of Russia" at scale 2.5M was compiled through the joint efforts of many pedologist around the country. Practically all scientific pedological centers and institutes in Russia contributed to the map their expertise and scientific knowledge accumulated during more than two decades. The map legend comprises the latest soil-genetic classification concepts in which soil characteristics have been considered in harmony with soil forming factors. The map soil-geographical background introduces a variety of geographical regularities of soil spatial distributions among which the soil zonality and the soil cover structure have been comprehensively represented. Although the "Soil Map of Russia at scale 2.5M" is regarded as the major inventory document at the country scale, it is not well known and introduced. The complexity of the legend and specific soil nomenclature have been the main confounding factors for the map implementation. To make the "Soil Map of Russia at scale 2.5M" accessible, the study relies on two basic documents, the "Revised Legend of the Soil Map of the World" (FAO, 1990) and the "Programme of the Soil Map of the USSR at scale 1:2.5M." The main purpose of the report is to introduce a complete, full and transparent correlation of the map legend with the FAO "Revised legend of the Soil Map of the World.

The IIASA-LUC Project Georeferenced Database of the Former USSR. Volume 5: Land Categories

The IIASA/LUC georeferenced database for the former U.S.S.R. was created within the framework of the project ``Modeling Land-Use and Land Cover Changes in Europe and Northern Asia" (LUC). For Russia, essential information on relief, soil, vegetation, land cover and use, etc. for routine environmental analysis was lacking when the LUC project started developing the database. In addition, the environmental data on the former U.S.S.R. which was available occurred in formats (papers, tables, etc.) that in general could not be used with modern information technology, and in particular in model building. In creating the LUC project database, we have achieved three objectives: 1) to obtain relevant information for the LUC project modeling exercises; 2) to develop data which are usable with modern information technology; 3) to contribute a series of digital databases which could be applied for various other analyses by the national and international scientific community. In defining the tasks it was agreed to create a set of digital databases which could be handled by geographic information systems (GIS). The full set of georeferenced digital databases was combined into the LUC project's GIS, using ARC/INFO. However, each individual item (physiography, soil, vegetation, etc.) was created as a unique specific digital database, allowing each item to be used separately, depending on users' needs. The complete series of these unique georeferenced digital databases for the territory of the former U.S.S.R. is described in the IIASA/LUC volumes: Volume 1 -- Physiography (landforms, slope conditions, elevations); Volume 2 -- Soil; Volume 3 -- Soil degradation status (Russia); Volume 4 -- Vegetation; Volume 5 -- Land categories; Volume 6 -- Agricultural regionalization

The LUC Approach to Creating a Continental-Scale Land-Cover Database for Russia

Land cover is an essential surface characteristic of the Earth. Yet -- this may come as a surprise -- there is no generally accepted, complete and universal land-cover product for Russia, as is the problem in many other parts of the world. A review of global land-cover databases concluded that one of the most pressing problems in global climate and ecosystem studies is a lack of adequate land-cover data. This may explain why land-cover mapping often leads to debate over classification schemes, use of class descriptors and labels, and product specifications. Land-use and land-cover information is required in various forms and at different scales. A variety of techniques are in current use to collect the necessary data, ranging from census studies, ground observations, to remotely sensed data. The methodological plurality has also resulted in a widely diverse number of methods to store and present these data. In view of this unsatisfactory situation, FAO and UNEP, with the support of UNESCO and a number of other organizations, have launched an initiative on harmonizing and standardizing land-use and land-cover classification systems. Another major effort has been launched by the International Geosphere-Biosphere Programme (IGBP), to serve the needs of the global environmental change research community. The IGBP-DIS Global 1 km Land-cover Project is currently underway. The project is primarily relying on NOAA AVHRR data and aims to develop and distribute a global data-set representing land-cover in terms of seventeen broad classes. Being aware of these efforts, and aiming to be consistent with and useful to the international research community, the Land-Use Change (LUC) project at IIASA decided at an early stage to be in active contact with the research groups charged with harmonizing land-use and land-cover classifications, to use their methods and standards as they would emerge. Consequently, as regards land-cover database development, the main task of the LUC project was defined as: (i) producing a complete list of land-cover categories in Europe and Northern Asia based on available national-level data sources, and (ii) which would correspond to the diversity of land-use and land-cover of this huge territory. Charged with this task, it was necessary to develop a framework allowing to concentrate the project's efforts on these problems. The objective of this paper is to present an outline and rationale of the methodology for elaborating the project's land-cover database. Comprising the major portion of the study region, the approach has been developed on the basis of Russian experience

A Land-Cover Classification for Modeling Natural Land Cover within the IIASA LUC Project

Natural forces have always shaped the global land cover, however resulting in mainly gradual changes. More recently anthropogenic impacts have resulted in fast changes and which dominate the natural impacts in many areas. Many studies to understand these changes and their consequences have been started. One common point of interest is the behavior and classification of the land cover. This kind of information is for example required within modeling activities, that intent to evaluate (for example climate change) impacts on land cover, scale independent. As result of the studies land cover information exists at different places around the world. However, although vegetation and land cover classifications exist already some time large differences have been found and no general accepted way of classification exists, e.g. in the level of detail. The land-cover datasets and the large number of classification systems/map legends differ in spatial resolution, definition, purposes, and outcome. For example the classifications use three different main bases: Eco-physiognomy (=relation between plant structure and its environment), environmental conditions (especially climate) and floristics. Coming up with a consistent classification is a common wish of many modelers. Therefore studies to harmonize the existing classifications have just recently started. Although they yet didn't have come up with the ultimate classification they recommended to start with coming up with a set of important attributes, and define these for the different classes. This is in agreement with other studies, which for example want to derive land cover from satellite data. The following step should be to develop a methodology through which the different classifications could be linked, by using these attributes. We are involved within the project "Modeling land-use/land-cover changes in Europe and Northern-Asia". Although is has not been our purpose to come up with a new land-cover classification, we developed a new list to integrate the land-cover diversity within the large region with small scale information as derived from e.g. case studies activities. In this paper we want describe how the land-cover classification for the modeling part of the project has been set up. First we give a short description of the project. Secondly, we come up with our definition of land cover, we indicate the requirements of a good classification and describe the attributes which are important within the classification. These attributes can be classified into internal, eco-physiognomic attributes, such as leaf phenology, and into environmental attributes. We agree with the UNEP harmonization project that such physiognomic attributes should be used for the basic definition of the classes, but it is our believe that for the evaluation of environmental impacts and for mapping purposes environmental attributes are also required

The IIASA-LUC Project Georeferenced Database of Russia. Volumes 1 and 2: Soil and Terrain Digital Database (SOTER)

The IIASA-LUC georeferenced database for the former U.S.S.R. was created within the framework of the project "Modeling Land Use and Land Cover Changes in Europe and Northern Asia" (LUC). For Russia, essential information on relief, soil, vegetation, land cover and use, etc., for routine environmental analysis was lacking when the LUC project started developing the database. In addition, the environmental data on the former U.S.S.R. which were available occurred in formats (papers, tables,etc.) that in general could not be used with modern information technology, and in particular in model building. In creating the LUC project database, we have established a threefold task: (1) to obtain the relevant information for the LUC project modeling excercises; (2) to develop data which is applicable to modern information technology; (3) to contribute a series of digital databases which could be applied for a number of other specific analyses by the national and international scientific community. In defining the tasks it was agreed to create a set of digital databases which could be handled by geographic information systems (GIS). The full set of georeferenced digital databases was combined into the LUC project's GIS, using ARC/INFO. However, each individual item (physiography, soil, vegetation, etc.) was created as a separate digital database, allowing each item to be used independently, according to user's needs. The complete set of the unique georeferenced digital databases for the territory of the former U.S.S.R. is described in the IIASA/LUC volumes: Volume 1 -- Physiography (landforms, slope conditions, elevations); Volume 2 -- Soil; Volume 3 -- Soil Degradation Status (Russia); Volume 4 -- Vegetation; Volume 5 -- Land Categories; Volume 6 -- Agricultural regionalization. The main objective of the research summarized in this report was to compile, fully correlate, and update the FAO Soil Map of the World for the territory of Russia. It originated from several discussions with Dr. W. Sombroek (FAO), R. Brinkman (FAO), R. Oldeman (ISRIC) which took place at the International Soil Reference Information Center (ISRIC) in 1988-1989. These discussions were initiated through research being carried out by the project on Global Assessment of Human-Induced Soil Degredation (UNEP/ISRIC, 1990) which urgently required reliable soil information on Russia. It was recognized that several other environment related activities were facing a similar problem. In response to the discussions, the Food and Agriculture Organization of the United Nations (FAO) launched a project in 1993. According to the Letter of Agreement (CMT 73197) signed by the FAO and Dokuchaev Soil Institute, the project was aimed at preparing "a Soil map of Russia at 1:5 million scale using the Revised Legend of the Soil Map of the World (1988) and corresponding database reflecting the information contained in the map of the same region." The Agreement defined six layers of information to be distinguished for digitizing: (1) Soil mapping unit boundaries; (2) Topographic lines (rivers, contour lines and coastal line); (3) Geographical coordinates (longitude, latitude); (4) Physiographic (landform) units; (5) Graticule of the map; (6) Province boundaries. In 1994, the requested products were completed and transferred to the FAO for digitizing by scanning. At that time, however, the compilation of a digital database could not be completed at FAO. In 1995 all materials were passed to the International Institute for Applied Systems Analysis (IIASA) with the objective to complete the database. Considerable efforts by the GIS group of the project "Modeling Land Use and Land Cover Changes in Europe and Northers Asia" at IIASA were put into checking, correcting, and linking the digital data, and making them mutually consistent. Completion of the digital database at IIASA, the first product of this kind to be published on the territory of Russia, has provided a more comprehensive understanding of the territory and its environment. Using modern GIS techniques, this knowledge is now readily available to any scientific or applied analyses of the land resources and environment of Russia