The author analyzes how existing representations of spatial phenomena in geography relate to the assumptions underlying statistical and geoinformatic methods. In a broad sense, geography problematizes multi scale manifestations of spatial homogeneity and heterogeneity, linking them to the spatial positions of observations. Models of geographic reduction are different ways of representing space, its elements, the spatial relationships among them, and the resulting spatial effects. These models determine how the positions of observations in space and the mechanisms of formation of spatial phenomena are described. The author considers three basic types of such representations (models)—fields, discrete objects, and networks—describing their key properties, providing examples from different subdisciplines of geography, and outlining differences in the application of spatial analysis and statistical methods such as kriging, movingwindow operations, spatial regression, and others. Models of reduction are discussed in greater detail using population geography and mobility as examples. In contrast to networkbased gravity models of mobility, which do not take the spatial context of movements into account, alternative interveningopportunities models are based on a topological description of potential movement destinations for agents, and the modeling results can be represented as a probability field of movements. Models of geographic reduction define the framework for formulating research questions and for applying statistical and geoinformatic methods. The same geographic phenomena can be represented simultaneously through different models, which opens up new ways of addressing research problems, while the methods that operate on these models can thus be transferred across different domains of geography.

This study, using data on the migration of 18-year-olds, analyzes the scale of migration flows between 160 cities—university centers in Russia. Migration at this age is highly intense and is primarily associated with young people moving to pursue higher education (bachelor’s or specialist’s degrees). Part of this flow consists of people moving from communities without universities and therefore lacking the opportunity to pursue higher education locally. Another group—the subject of this study—has these opportunities but chooses to study in other cities, based on personal perceptions of their hometowns and the options for obtaining vocational training there and in other cities and universities, as well as other individual motivations. An analysis of the mutual migration flows between the country’s educational centers allows us to construct a hierarchy of migration flows, represented by seven levels. The basis for this analysis is the intercity migration growth (loss) and migration turnover indicators, calculated using a 160 × 160 migration matrix. The results showed that, along with Moscow and St. Petersburg, Tomsk is the largest educational center. Tomsk, not Novosibirsk, Krasnoyarsk, or Vladivostok, accounts for the third largest number of positive migration links. Despite Moscow’s more than twofold population advantage over St. Petersburg, its lead in capturing educational migration flows from competing educational centers is not as overwhelming: it accounts for 44.3% of migration turnover, while St. Petersburg accounts for 40.3%. The hierarchy of cities is determined by the logic of the hierarchical administrative-territorial structure, the size of cities, and their (and the regions they lead) role in interregional migration in the Russian socioeconomic system.

This paper examines the territorial dynamics and key aspects of the structural transformation of the Russian tire industry. The research dataset includes statistical data on tire production at the enterprise level, foreign trade data, business press materials, company reports, and thematic geographic and economic studies. The paper illustrates how the content and scale of the consumer factor in enterprise location changed from the district level to the national and macroregional levels. As the share of transportation costs in the shipment of tires decreased, the principle of enterprise placement focused on supplying districts gave way to the practice of locating enterprises in large urban agglomerations of European Russia. At the same time, the importance of preferential regimes for specific production sites increased. The macroregional territorial shifts that were typical of the Soviet period—from central regions to peripheral areas—have been replaced by reverse shifts toward the Central and Northwestern regions. Calculations of the redistribution coefficient and the location mobility index confirm the temporal heterogeneity of the industry’s territorial dynamics. The most intensive change in the territorial structure occurred from 2004 to 2012 against the backdrop of the closure of old production facilities and the placement of foreign companies’ enterprises. The study demonstrates a deepening specialization of tire industry enterprises based on the calculation of the weighted Ryabtsev and Herfindahl–Hirschman indices. The key patterns of organizational change in the industry have been identified. These include the high dynamism of organizational structure, the low stability of horizontal and vertical integration structures due to the small scale of the Russian market, and the peripheral role of the industry for petrochemical companies. Additionally, there is greater stability in global integration projects and large-scale, horizontally integrated structures. From the 2000s to the 2010s, the Russian tire industry developed an export orientation alongside a simultaneous increase in imports. In the context of the forced reduction of exports after 2022, the key task is to reorient production toward the domestic market and reduce the import dependence of the market, which is a prerequisite for restoring production volumes.

To analyze the uneven distribution of the People’s Republic of China highway network (expressways and Class 1 and Class 2 roads) in dynamics (2014–2022), unique fractional territorial statistics for 334 cells (districts), available only in Chinese, as well as cartometric calculations using data from the Open Street Map service, were used. This made it possible to compile very detailed maps of the density of highways, which revealed geographical differences in the level of transport development of the territory of China, which are not visible on ordinary maps and even in the national atlas of the People’s Republic of China. The main areas of development of the road network and the cores of its concentration, as well as spatial gaps in the pattern of this development, have been identified. The main areas of concentration of the road network include the most developed and populated urban agglomerations—the Beijing-Tianjin metropolitan area, the Shanghai agglomeration, the Pearl River Delta agglomeration and the Sichuan Basin. The density of roads has increased most noticeably in the central and western regions of the country with significantly lower population density and lower level of economic development. Based on calculations, the main impact on the increase in highway density in 2014–2022 was caused by the density of the population and the desire to increase connectivity between the centers and neighboring districts, rather than the size of their GRP. The length of the road network increased by one third during this period, and the coverage area of the territories adjacent to the main areas of concentration of the road network significantly expanded.

The characteristics of the disturbance of agricultural landscapes of the Plain Crimea by erosion processes in modern conditions are given. Two groups of factors have been identified that determine the manifestation of soil erosion processes: natural and anthropogenic. Among natural processes, considerable attention is paid to the variability of climatic characteristics. The territory of the Plain Crimea is characterized by an increase in temperature, mainly due to the winter months. It is noted that about 80–85% of the annual precipitation has a pronounced rainfall nature, which leads to the intensification of water erosion processes. Analysis of complex indicators of aridity showed that the entire territory of the Crimean Plain, according to the Torthwaite aridity index, is characterized by arid and super–arid conditions, which intensify when moving from the west to the northeast and east of the region. Agricultural yields also are changed from west to east. A significant contribution to the processes of soil erosion is made by droughts, hot winds, and dust storms, the number of which has increased in recent years, which, against the backdrop of an extremely high degree of plowing of the territory, leads to catastrophic loss of soil. According to calculations, soil loss because of dust storms is hundreds of times higher than the permissible erosion standards for zonal soils of the territory under consideration. An assessment of the condition of forest belts in municipal areas of the Crimean plain was carried out. To comprehensively characterize the soil and ecological state of the region, an assessment of the potential danger of desertification was carried out. It is noted that almost all areas of the Crimean Plain are exposed to the danger of desertification, but the western and central areas of the region are subject to the greatest dangers of desert–forming processes.

Based on expeditionary sampling in different seasons of 2024 and using a set of 80 hydrochemical and hydrobiological indicators, the current ecological state of the snow-glacier cover, surface water runoff, and lake water on Alexandra Land Island, located in the western part of the Franz Josef Land Archipelago, has been assessed. There is no economic activity in areas where ice domes develop. These domes cover more than 85% of the island. This mainly affects land areas that are free of ice. However, the damage to the natural environment has largely been eliminated through cleanup measures. The elemental composition, pH, and COD (chemical oxygen demand) indicators, as well as the mineralization and content of ammonium, nitrites, nitrates, phosphates, and petroleum products, were determined for snow, snow-ice melt runoff, and lake water. Two biotests were used to assess the hydrobiological properties of the aquatic environment: the ciliate Tetrahymena pyriformis (Tp) and the microalgae Chlorella vulgaris Beijer (Cvb). No toxicity towards hydrobionts in the aquatic environment was detected. Chemical analysis of the samples revealed that the concentration of nitrogen and phosphorus compounds in the island’s aquatic environment does not exceed the maximum permissible concentration. The concentration of metals in snow, ice, and meltwater on glaciers does not exceed regulatory limits. However, when this meltwater comes into contact with the ground and accumulates in lakes, the concentration of copper, aluminum, and iron increases. In some cases, the concentration levels of these elements exceeded the established maximum by tens of times, likely due to natural causes. No contamination of water bodies by petroleum products was found. Currently, the island’s hydroecological state generally corresponds to background Arctic natural and climatic conditions.

An overview of modern approaches to the study of drainage basins is provided, which can form the basis of a comprehensive geoecological assessment of the territory. The algorithm for such an assessment is presented, comprising five main steps. The proposed approach may enable the creation of a reliable framework for the further expansion or specialisation of analysis of the territory, and the development of recommendations for optimizing land and water use within a small drainage basin. To illustrate the research algorithm, two small drainage basins in Kursk Oblast are used as examples. They are comparable in area (both measuring about 3.2 km²) but have different morphological structures. Taking the dynamics of water discharges into account shows differences in the nature of erosion and accumulation processes in the catchments. The landscape scheme made it possible to assess the disturbance of landscapes. The basin adjacent to the city has a high proportion of moderately disturbed landscapes, and the more remote one has slightly disturbed landscapes. Socioeconomic activity in the surrounding area affects erosionaccumulative processes and disturbance of the landscape structure of basins in different ways. The greatest environmental stress is created by the road running along the watershed between the basins and the landfill site in the upper reaches of one of them.

Russia, India, and China (RIC) are the world’s largest emitters of anthropogenic CO₂, accounting for over 40% of global emissions. Their emissions have increased exponentially over the past 20 years (excluding Russia). At the same time, these countries are pursuing policies to limit emissions, as reflected in their official programs submitted to the UNFCCC. They are experiencing sectoral decarbonization and low-carbon transformation processes, each with its own national specifics. The countries intend to achieve carbon neutrality by 2060–2070. An analysis of sectoral carbon intensity dynamics allows us to identify the national characteristics of decarbonization, its achievements, and challenges. The objective of this study is to determine the sectoral specifics of emissions and decarbonization processes in Russia, India, and China, and to demonstrate the differences and similarities in the trajectories of the transition to a low-carbon economic development model. The energy and carbon intensity of RIC economies is twice that of the countries in the global center. Simultaneously, decoupling processes between economic growth and CO₂ emissions are observed. Energy, industry, and transport are the main carbon emitters in the RIC. The sectoral structure of RIC emissions differs significantly from that of the global Core and Periphery. Differences in sectoral carbon intensity and its dynamics are observed among RIC countries. The low-carbon transition has its own national characteristics, driven by economic, geographical, and political factors.

The interrelated and interdependent development of vegetation and soils during primary ecogenetic successions in quarries used for the extraction of building materials in the southern shrub tundra of northeastern European Russia (near Vorkuta) was investigated. The studied quarries were characterized by a varying duration time of spontaneous overgrowth, different substrate textures (loams, sands, sands with gravel) and moisture content. The analysis of species composition, structure of plant communities, and soil morphology of 61 sample plots allowed us to describe the course of xerarchic, mesarchic, and hydrarchic primary succession types. During the first six decades of spontaneous overgrowth, no formation of typical tundra vegetation or soils characteristic of subarctic regions was observed within the quarries. Humus psammozems were described in xeromorphic ecotopes under cryptogamic and lichen communities. Pelozems and psammozems formed under mesomorphic conditions under herb-moss communities with willow. Soils belonging to the Gleyic order (peat-gley soils) were recorded in hydromorphic ecotopes under sedge/horsetail-moss willow stands. Under drained conditions, distinct organogenic horizons (litters) were observed in quarry soils. Loamy soils showed weak gleying in the upper part of the profile, while gravelly-sandy and sandy soils exhibited alpha-humus processes. Waterlogged soils were characterized by the development of peat formation, humus leakage, and gleying. Cryogenesis (cryogenic sorting of material, cryogenic soil cracking, cryoturbation, and the formation of medallion-shaped spots and tubercles) was recorded in the quarry areas. The formation of plant communities contributed to the stabilization of the quarry substrate and determined the accumulation of soil organic carbon. As in background soils, C_org reserves in quarry soils increased along with the increasing soil moisture content. Under low-productivity closed communities of xeromorphic ecotopes, C_org reserves in soils were eight times lower than in background soils with comparable moisture levels. Under rapidly developing closed communities of hydromorphic quarry ecotopes, the value was half that of the background soil.

The article examines the spatial and temporal features of population settlement and its impact on the environment within the Azov-Lower Don coastal (coastal and riverine) areas of the Rostov region for the period between the 2010 and 2021 censuses, as well as the three subsequent years marked by the Special Military Operation in neighboring regions. In methodological terms, based on the works of researchers of “marine” socio-geographical issues, who summarized domestic and foreign experience in localizing the boundaries of the coastal zone, municipalities with direct access to the waters of the Azov Sea, the Tsimlyansk Reservoir and the Lower Don floodplain, and concentrating almost 2/3 of the regional population, are identified. Over the period under consideration, their total population increased by 2.7%. The coastal municipalities that are part of the Rostov agglomeration and directly adjacent to it were characterized by the highest population density in 2011–2024. An analysis of population density dynamics at the district and urban district levels yielded no new results, but confirmed trends noted by previous researchers. At the same time, examining population distribution dynamics at a “miniature” scale — at the level of rural and urban coastal settlements — revealed significant intra-district disparities, particularly the presence of municipalities most susceptible to depopulation and intense residential development. Internal disparities in population distribution have been recorded throughout the Azov-Lower Don coastal districts. The coronavirus pandemic has significantly impacted the intensity of suburbanization processes characteristic of Rostov-on-Don and Taganrog. The residential appeal of the region’s coastal rural settlements is determined by their proximity to the most economically and socially infrastructurally developed large cities and is virtually independent of natural-recreational, and environmental factors.

The lack of knowledge about the Novaya Zemlya reindeer (Rangifer tarandus pearsoni) once led to the common belief that the archipelago was inhabited by a feral, domesticated subspecies that differed in appearance and behaviour from the so-called indigenous Novaya Zemlya reindeer. However, this view failed to consider various natural factors that could explain such differences, such as the islands’ significant size and diverse landscapes. This study aims to evaluate the potential biogeographical factors that resulted in reindeer being present on the Novaya Zemlya Archipelago, despite them initially differing in appearance. The distribution of Novaya Zemlya reindeer across different eras was determined based on literature sources, reflecting the archipelago’s environmental research history and the animals’ occupation of various landscapes from the 16th to the 20th century. For the first time, an attempt has been made to estimate the size of the reindeer population in Novaya Zemlya Archipelago based on data from harvested individuals. The existence of landscape refugia on Severny Island is discussed as an explanation for the differences in the reindeer’s physical appearance. Similarities are drawn with other subspecies and ecological groups of Arctic insular wild reindeer. This includes the ability of Novaya Zemlya reindeer to migrate or remain within a relatively small permanent habitat on a single island. The theory that Novaya Zemlya Archipelago is inhabited by two genetically distinct reindeer populations, which differ in morphology and behaviour, can be explained by the archipelago’s biogeographical characteristics.

During the anniversaries of outstanding 20th-century Russian geographers and academicians L.S. Berg, S.V. Kalesnik, I.P. Gerasimov, and K.K. Markov, the unique phenomenon of continuity of knowledge in the “teacher–student” system is considered from different perspectives. L.S. Berg educated many scientists and encyclopediasts who continued the work of V.V. Dokuchaev and D.N. Anuchin. In the 1920s and 1940s, he launched the careers of many exceptional geographical scientists who established the foundation of modern geographical science and its primary branches, including geomorphology, paleogeography, soil geography, landscape science, and biogeography. The stages of development of their research, achievements in various fields of science, contribution to the Victory in the Great Patriotic War, the role of the academic and university environment and participation in public life, both teachers and students, are shown in comparative terms. The article provides a comparative assessment of the contribution of the Teacher and his students to the development of the earth science (geosphere) and landscape branches of academic and university geography. These branches were established at the beginning of the 20th century and represent the convergence and harmonization of the Leningrad and Moscow schools. 

Veniamin Petrovich Semenov-Tyan-Shansky (1870–1942, hereinafter V.P.) is an outstanding Russian geographer, cartographer and statistician, as well as a geologist and landscape artist. His strong point within geography was anthropogeography and theoretical geography. He was one of the first in the world to raise the question of the aesthetic resources of nature and the relationship between art, in all the breadth of its genre palette, and science, in particular — and especially — geography. Both the landscape scientistgeographer and the landscape artist — both, in his view, think in the same geographical images, both are engaged in identifying both typical and unique features in them: only the artist is artistic, subjective and, if possible, talented, while the geographer is scientific, objective and reliable. Being the founder, director and one of the landscape artists of the Central Geographical Museum (CGM), which skillfully and systematically visualized geographical landscapes, V.P. was a unique case of the synthesis of science and art, geography and painting. The dominant motif of V.P. as an artist is landscape landscapes. Most often he painted from life, but sometimes he also practiced copying from suitable photographs. After the liquidation of the CGM, its exposition and funds were largely lost. Among what survived, V.P. is credited with about 30 works, and in total for the CGM, according to N.N. Baransky, he painted about 140 of them. About 150 paintings and sketches by V.P. have been preserved in private hands — in the collections of members of the Semenov-Tyan-Shansky family. In total, the V.P. contains 195 works of art, 27 of which have a background from the Central State Museum funds. The corpus is dispersed across 15 collections, 13 of which are in St. Petersburg and one by one in Ryazan and in the village of Gremyachka in Ryazan Oblast. Characteristics of each collection are given in the article.

The purpose of this article is to develop a unified classification system for natural and human-made geographical complexes (geocomplexes) in different geospheres. The geocomplex concept is accepted in the general geographical sense and includes human populations, the processes and results of their activities, and natural components and processes. Ten criteria are considered for the classification of geocomplexes: the degree of naturalness/artificiality (or transformation); location in geospheric layers; location in geospheric sublayers; zonal and sectoral location; genus of human population activity; species of human population activity; structure of technical cover; aggregate state of water and type of water or ice body; presence or absence of magmatism; location in structural units of the lithosphere. These interconnected, complementary criteria create a classification space for categorising the full range of geocomplexes. Using classification criteria as an axis in a multidimensional feature space leads to the ordering of classes and the formation of an ordination-classification system. Eighty-six classes of the third rank are distinguished: forty-three natural and forty-three anthropogenic (techno-natural, naturaltechnical and technical) ones. Examples of classes of natural geocomplexes are terrestrial polar, coastal and shallow-water equatorial-tropical, deep-water pelagic (oceanic, marine), lake and river (continental) bottom extratropical, underwater and subglacial volcanic, cave, crustal continental. Examples of anthropogenic geocomplexes include industrial underground areas with dense technical infrastructure, urban areas with high-rise and multi-storey buildings, agricultural areas with aquaculture, transport areas with aerial infrastructure, sacred areas in natural environments, and museumified natural-technical areas. In order to classify the full range of geocomplexes, it is necessary to consider a variety of geographical and related scientific concepts, as well as different types of practical activity. A key outcome of the classification process is the clarification of the meaning of many terms embedded within the classification system.