The IIASA-LUC Project Georeferenced Database of the Former U.S.S.R., Volume 4: Vegetation

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 exercises; (2) to develop data which is applicable to modem 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 users' needs. The complete series 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

Commercialization of the nature-resource potential of anthropogenic objects (on the example of exhausted mines and quarries)

Abstract. In this article we developed scientific and applied foundations of commercialization of the nature-resource potential of anthropogenic objects, on the example of exhausted mines. It is determined that the category of “anthropogenic object” can be considered in a narrow-applied sense, as specific anthropogenic objects to ensure the target needs, and in a broad theoretical sense, meaning everything that is created and changed by human influence, that is the objects of both artificial and natural origin. It was determined that problems of commercialization of the natural-resource potential of anthropogenic objects are most often considered by researchers for specific objects, without having complex methodological coverage from the point of view of combining environmental, technical, economic and managerial components. When studying the substantiation of the scientific base, the authors confirmed the feasibility of the commercialization of natural-resource potential of anthropogenic objects on the example of a number of theoretical scientific studies in reclamation, reconstruction, recreation, remediation, restoration of biological productivity and economic value of land disturbed by economic activity. The considered examples of exhausted mines in the 21st century in the USA, Canada, Germany, Romania, and Poland indicate a wide range of opportunities for their commercialization. The study of the potential for commercialization of exhausted mines in the post-Soviet countries testified to the underused reserves for the commercialization of their nature-resource potential and their high potential for further development. The authors proposed the identification of anthropogenic objects on the basic livelihood spheres of society. There were identified the main system (natural, biological, technical, economic, social, managerial) and structural (subjects, trends, threats, risks, problems, challenges) factors of diagnosing the state of an anthropogenic object. A set of measures has been developed for commercialization of an anthropogenic object in functional and production activities, product policy, financial and investment spheres, pricing and sales policies, promotion, management and determination of property rights. Recommendations were provided on optimizing the management decision-making process based on a set of positivistic development principles, methods, and management functions. The study allows international organizations, state and local authorities, territorial communities, owners and potential investors to see new opportunities and make mutually beneficial decisions on the rational use of the nature-resource potential of anthropogenic objects

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 Petrophytic Steppes of the Urals: Diversity and Ecological Drivers

The diversity and main compositional patterns of the petrophytic steppes of the Urals were studied. Two questions were considered in detail: (i) How rich is the phytocoenotic diversity of the petrophytic steppes? and (ii) What kind of ecological drivers determine its differentiation? A dataset of 1,025 relevés was compiled,representing communities of different climatic and geological conditions. Using formalized classification (TWINSPAN algorithm), eight vegetation types on the petrophytic steppes were defined. DCA-ordination was used to determine the main ecological drivers (both climatic and edaphic) of plant communities’ diversity. Among them are mean annual temperature and precipitation, aridity, rockiness and local habitat moisture. The interaction of different ecological and geographical factors leads to high levels of floristic and coenotic diversity of vegetation in dry rocky habitats. Keywords: petrophytic steppes, ecological drivers, ordination, Southern Ural

Analysis of rare type of plants from botanical graden collection at SRU “Belsu” (Belgorod, Russia)

The aim of the study was the comprehensive analysis of rare plants from the collection fund of the botanical garden at the National Research University “BelSU