52 research outputs found
Spatial differences in dissolved silicon utilisation in Lake Baikal, Siberia: examining the impact of high diatom biomass events and eutrophication
Recent research has highlighted how Lake Baikal, Siberia, has responded to the direct and indirect effects of climate change (e.g., ice-cover duration), nutrient loading, and pollution, manifesting as changes in phytoplankton/zooplankton populations, community structure, and seasonal succession. Here, we combine and compare= analyses of chlorophyll a (an estimate of total algal biomass), carotenoid pigments (biomarkers of algal groups), and lake water silicon isotope geochemistry (d30SiDSi) to differentiate spatial patterns in dissolved silicon (DSi) uptake at Lake Baikal. A total of 15 sites across the three basins (south, central, and north) of Lake Baikal were sampled in August 2013 along a depth gradient of 0β180 m. Strong, significant correlations were found between vertical profiles of photic zone DSi concentrations and d30SiDSi compositions (r 5 20.81, p < 0.001), although these are strongest in the central basin aphotic zone (r 5 20.98, p < 0.001). Data refute the hypothesis of DSi uptake by picocyanobacteria. Algal biomass profiles and high surface d30SiDSi compositions suggest greater productivity in the south basin and more oligotrophic conditions in the north basin. d30SiDSi signatures are highest at depth (20 m) in central basin sites, indicating greater (10β40%) DSi utilization at deep chlorophyll maxima. DSi limitation occurs in the pelagic central basin, probably reflecting a high diatom biomass bloom event (Aulacoseira baicalensis). Meanwhile in the more hydrologically restricted, shallow Maloe More region (central basin), both high d30SiDSi compositions and picocyanobacteria (zeaxanthin) concentrations, respectively point to the legacy of an βAulacoseira bloom yearβ and continuous nutrient supply in summer months (e.g., localized eutrophication)
Sinking properties of some phytoplankton shapes and the relation of form resistance to morphological diversity of plankton β an experimental study
Form resistance (Phi) is a dimensionless number expressing how much slower or faster a particle of any form sinks in a fluid medium than the sphere of equivalent volume. Form resistance factors of PVC models of phytoplankton sinking in glycerin were measured in a large aquarium (0.6 x 0.6 x 0.95 m). For cylindrical forms, a positive relationship was found between Phi and length/ width ratio. Coiling decreased Phi in filamentous forms. Form resistance of Asterionella colonies increased from single cells up to 6-celled colonies than remained nearly constant. For Fragilaria crotonensis chains, no such upper limit to Phi was observed in chains of up to 20 cells ( longer ones were not measured). The effect of symmetry on Phi was tested in 1 - 6-celled Asterionella colonies, having variable angles between the cells, and in Tetrastrum staurogeniaeforme coenobia, having different spine arrangements. In all cases, symmetric forms had considerably higher form resistance than asymmetric ones. However, for Pediastrum coenobia with symmetric/asymmetric fenestration, no difference was observed with respect to symmetry. Increasing number and length of spines on Tetrastrum coenobia substantially increased Phi. For a series of Staurastrum forms, a significant positive correlation was found between arm-length/cell-width ratio and Phi: protuberances increased form resistance. Flagellates (Rhodomonas, Gymnodinium) had a Phi 1. The highest value ( Phi = 8.1) was established for a 20-celled Fragilaria crotonensis chain. Possible origin of the so-called 'vital component' ( a factor that shows how much slower viable populations sink than morphologically similar senescent or dead ones) is discussed, as is the role of form resistance in evolution of high diversity of plankton morphologies
Modeling the Interaction of the Regions of Russia and the Republic of Belarus in the Sphere of the Processing Industry
In connection with the processes of the formation of the Union State of Russia and Belarus, the relevance of conducting a study of economic, infrastructural and institutional factors affecting the change in the level of economic interaction between the regions of the Russian Federation and the Republic of Belarus is increasing. The aim of the work is to carry out spatial modeling of the possible interaction of the regions of the Russian Federation and the Republic of Belarus in the manufacturing industry and to assess the factors affecting this interaction. The main hypothesis of the study is the assumption that the elements of the matrix of interregional interactions are proxy variables that characterize the degree of this interaction. At the first stage, the spatial distribution of the volume of output in the manufacturing sector of the regions of the two countries is investigated in order to assess possibilities of interaction between the regions in this sector. In modeling, the Republic of Belarus is considered as a separate region within the Union State. Calculations of the global and local Moranβs indices have been carried out and possible spatial autocorrelations have been determined, both between the regions of the Russian Federation and between the regions of these two countries. In this study, economic indicators calculated on the basis of inverse values of the difference in interregional gross regional products were selected as elements of the weight matrix. At the second stage, the influence of economic, infrastructural and institutional factors on the indicator characterizing the degree of possible interaction of the regions of the two countries in the manufacturing industry was studied. Using quantile regression, the influence of economic, infrastructural and institutional factors on this investigated indicator was studied. The use of this approach makes it possible to substantiate the priority directions of economic development of the territories within the framework of the Union State and, in particular, to search for centers of attraction of resources and spheres of their influence on the territory. The results of the work can be used in preparation of strategies, programs and schemes for the placement and development of industries, taking into account the potential of a new level of integration of the economies of Russia and Belarus.Π ΡΠ²ΡΠ·ΠΈ Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ°ΠΌΠΈ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π‘ΠΎΡΠ·Π½ΠΎΠ³ΠΎ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π° Π²ΠΎΠ·ΡΠ°ΡΡΠ°Π΅Ρ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ
Π½Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠΎΠ²Π½Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ ΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ΅Π»Π°ΡΡΡΡ. Π¦Π΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ ΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ΅Π»Π°ΡΡΡΡ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ
Π½Π° ΡΡΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΠ΅. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ Π³ΠΈΠΏΠΎΡΠ΅Π·ΠΎΠΉ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠ΅Π΄ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ ΠΎ ΡΠΎΠΌ, ΡΡΠΎ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ ΠΌΠ°ΡΡΠΈΡΡ ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΠΉ ΡΠ²Π»ΡΡΡΡΡ ΠΏΡΠΎΠΊΡΠΈ-ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΠΈ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠΌΠΈ ΡΡΠ΅ΠΏΠ΅Π½Ρ ΡΡΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΡ. ΠΠ° ΠΏΠ΅ΡΠ²ΠΎΠΌ ΡΡΠ°ΠΏΠ΅ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΡΡΡ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΎΠ±ΡΠ΅ΠΌΠ° Π²ΡΠΏΡΡΠΊΠ° Π² ΡΠ΅ΠΊΡΠΎΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΡΠΊΠ°Π·Π°Π½Π½ΡΡ
ΡΡΡΠ°Π½ Ρ ΡΠ΅Π»ΡΡ ΠΎΡΠ΅Π½ΠΊΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΡΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π² Π΄Π°Π½Π½ΠΎΠΌ ΡΠ΅ΠΊΡΠΎΡΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. ΠΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ° ΠΠ΅Π»Π°ΡΡΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΊΠ°ΠΊ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠΉ ΡΠ΅Π³ΠΈΠΎΠ½ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π‘ΠΎΡΠ·Π½ΠΎΠ³ΠΎ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π°. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Ρ ΡΠ°ΡΡΠ΅ΡΡ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈ Π»ΠΎΠΊΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΠ½Π΄Π΅ΠΊΡΠΎΠ² ΠΠΎΡΠ°Π½Π° ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΠ΅ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΡΠ΅ Π°Π²ΡΠΎΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΈ ΠΊΠ°ΠΊ ΠΌΠ΅ΠΆΠ΄Ρ ΡΡΠ±ΡΠ΅ΠΊΡΠ°ΠΌΠΈ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ, ΡΠ°ΠΊ ΠΈ ΠΌΠ΅ΠΆΠ΄Ρ ΡΠ΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ ΡΠΊΠ°Π·Π°Π½Π½ΡΡ
ΡΡΡΠ°Π½. Π ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠΌΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² Π²Π΅ΡΠΎΠ²ΠΎΠΉ ΠΌΠ°ΡΡΠΈΡΡ Π²ΡΠ±ΡΠ°Π½Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ, ΡΠ°ΡΡΡΠΈΡΠ°Π½Π½ΡΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠ±ΡΠ°ΡΠ½ΡΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ ΡΠ°Π·Π½ΠΈΡΡ ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π²Π°Π»ΠΎΠ²ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ². ΠΠ° Π²ΡΠΎΡΠΎΠΌ ΡΡΠ°ΠΏΠ΅ ΠΈΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠΉ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΡΠΊΠ°Π·Π°Π½Π½ΡΡ
ΡΡΡΠ°Π½ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. Π‘ ΠΏΠΎΠΌΠΎΡΡΡ ΠΊΠ²Π°Π½ΡΠΈΠ»ΡΠ½ΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΠΈΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΡΡΠΎΡ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΠΉ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°ΡΡ ΠΏΡΠΈΠΎΡΠΈΡΠ΅ΡΠ½ΡΠ΅ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π‘ΠΎΡΠ·Π½ΠΎΠ³ΠΎ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π°, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²ΠΈΡΡ ΠΏΠΎΠΈΡΠΊ ΡΠ΅Π½ΡΡΠΎΠ² ΠΏΡΠΈΡΡΠΆΠ΅Π½ΠΈΡ ΡΠ΅ΡΡΡΡΠΎΠ² ΠΈ ΡΡΠ΅Ρ ΠΈΡ
Π²Π»ΠΈΡΠ½ΠΈΡ Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°Π±ΠΎΡΡ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΏΡΠΈ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ΅ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΉ, ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ ΠΈ ΡΡ
Π΅ΠΌ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΎΡΡΠ°ΡΠ»Π΅ΠΉ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»Π° Π½ΠΎΠ²ΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊ Π ΠΎΡΡΠΈΠΈ ΠΈ ΠΠ΅Π»ΠΎΡΡΡΡΠΈΠΈ.Π ΡΠ²ΡΠ·ΠΈ Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ°ΠΌΠΈ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π‘ΠΎΡΠ·Π½ΠΎΠ³ΠΎ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π° Π²ΠΎΠ·ΡΠ°ΡΡΠ°Π΅Ρ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ
Π½Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠΎΠ²Π½Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ ΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ΅Π»Π°ΡΡΡΡ. Π¦Π΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ ΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ΅Π»Π°ΡΡΡΡ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ
Π½Π° ΡΡΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΠ΅. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ Π³ΠΈΠΏΠΎΡΠ΅Π·ΠΎΠΉ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠ΅Π΄ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ ΠΎ ΡΠΎΠΌ, ΡΡΠΎ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ ΠΌΠ°ΡΡΠΈΡΡ ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΠΉ ΡΠ²Π»ΡΡΡΡΡ ΠΏΡΠΎΠΊΡΠΈ-ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΠΈ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠΌΠΈ ΡΡΠ΅ΠΏΠ΅Π½Ρ ΡΡΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΡ. ΠΠ° ΠΏΠ΅ΡΠ²ΠΎΠΌ ΡΡΠ°ΠΏΠ΅ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΡΡΡ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΎΠ±ΡΠ΅ΠΌΠ° Π²ΡΠΏΡΡΠΊΠ° Π² ΡΠ΅ΠΊΡΠΎΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΡΠΊΠ°Π·Π°Π½Π½ΡΡ
ΡΡΡΠ°Π½ Ρ ΡΠ΅Π»ΡΡ ΠΎΡΠ΅Π½ΠΊΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΡΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π² Π΄Π°Π½Π½ΠΎΠΌ ΡΠ΅ΠΊΡΠΎΡΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. ΠΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ° ΠΠ΅Π»Π°ΡΡΡΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΠΊΠ°ΠΊ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠΉ ΡΠ΅Π³ΠΈΠΎΠ½ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π‘ΠΎΡΠ·Π½ΠΎΠ³ΠΎ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π°. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Ρ ΡΠ°ΡΡΠ΅ΡΡ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈ Π»ΠΎΠΊΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΠ½Π΄Π΅ΠΊΡΠΎΠ² ΠΠΎΡΠ°Π½Π° ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΠ΅ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΡΠ΅ Π°Π²ΡΠΎΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΈ ΠΊΠ°ΠΊ ΠΌΠ΅ΠΆΠ΄Ρ ΡΡΠ±ΡΠ΅ΠΊΡΠ°ΠΌΠΈ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ, ΡΠ°ΠΊ ΠΈ ΠΌΠ΅ΠΆΠ΄Ρ ΡΠ΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ ΡΠΊΠ°Π·Π°Π½Π½ΡΡ
ΡΡΡΠ°Π½. Π ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠΌΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ² Π²Π΅ΡΠΎΠ²ΠΎΠΉ ΠΌΠ°ΡΡΠΈΡΡ Π²ΡΠ±ΡΠ°Π½Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ, ΡΠ°ΡΡΡΠΈΡΠ°Π½Π½ΡΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠ±ΡΠ°ΡΠ½ΡΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ ΡΠ°Π·Π½ΠΈΡΡ ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π²Π°Π»ΠΎΠ²ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ². ΠΠ° Π²ΡΠΎΡΠΎΠΌ ΡΡΠ°ΠΏΠ΅ ΠΈΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠΉ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΡΠΊΠ°Π·Π°Π½Π½ΡΡ
ΡΡΡΠ°Π½ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. Π‘ ΠΏΠΎΠΌΠΎΡΡΡ ΠΊΠ²Π°Π½ΡΠΈΠ»ΡΠ½ΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΠΈΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΡΡΠΎΡ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΠΉ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°ΡΡ ΠΏΡΠΈΠΎΡΠΈΡΠ΅ΡΠ½ΡΠ΅ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π‘ΠΎΡΠ·Π½ΠΎΠ³ΠΎ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π°, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²ΠΈΡΡ ΠΏΠΎΠΈΡΠΊ ΡΠ΅Π½ΡΡΠΎΠ² ΠΏΡΠΈΡΡΠΆΠ΅Π½ΠΈΡ ΡΠ΅ΡΡΡΡΠΎΠ² ΠΈ ΡΡΠ΅Ρ ΠΈΡ
Π²Π»ΠΈΡΠ½ΠΈΡ Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°Π±ΠΎΡΡ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΏΡΠΈ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ΅ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΉ, ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ ΠΈ ΡΡ
Π΅ΠΌ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΎΡΡΠ°ΡΠ»Π΅ΠΉ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»Π° Π½ΠΎΠ²ΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊ Π ΠΎΡΡΠΈΠΈ ΠΈ ΠΠ΅Π»ΠΎΡΡΡΡΠΈΠΈ.The study was supported by the RFBR grant 20-510-0002 (Bel_a) Β«Tools for assessing the interaction of the regions of Russia and Belarus in industrial and technological development and substantiating its priorities in the context of deepening integration processes and global challengesΒ».ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ ΠΏΡΠΈ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ΅ Π³ΡΠ°Π½ΡΠ° Π Π€Π€Π 20-510-0002 (ΠΠ΅Π»_Π°) Β«ΠΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ Π² Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π ΠΎΡΡΠΈΠΈ ΠΈ ΠΠ΅Π»Π°ΡΡΡΠΈ Π² ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎ-ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΠ°Π·Π²ΠΈΡΠΈΠΈ ΠΈ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΡ Π΅Π³ΠΎ ΠΏΡΠΈΠΎΡΠΈΡΠ΅ΡΠΎΠ² Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠ³Π»ΡΠ±Π»Π΅Π½ΠΈΡ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΠΈ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΡΡ
Π²ΡΠ·ΠΎΠ²ΠΎΠ²Β»
Assessment of Energy Supply to the Yamal Peninsula Based on Fuzzy Multicriteria Analysis
ΠΠ°ΠΆΠ½Π΅ΠΉΡΠΈΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠ΅ΠΌ ΠΏΠΎΠ»Π½ΠΎΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π²ΠΎΠ²Π»Π΅ΡΠ΅Π½ΠΈΡ Π²Π½ΠΎΠ²Ρ ΠΎΡΠ²Π°ΠΈΠ²Π°Π΅ΠΌΠΎΠΉ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΠ΅ Π΅Π΅ ΠΏΠΎΠ»Π΅Π·Π½ΠΎΠΉ ΡΠ½Π΅ΡΠ³ΠΈΠ΅ΠΉ. ΠΠ»Ρ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ Π½ΠΎΠ²ΠΎΠ³ΠΎ ΠΎΡΠ²ΠΎΠ΅Π½ΠΈΡ, ΡΠ°ΠΊΠΈΡ
ΠΊΠ°ΠΊ ΠΏΠΎΠ»ΡΠΎΡΡΡΠΎΠ² Π―ΠΌΠ°Π», ΡΡΡΠ΅ΡΡΠ²ΡΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π°Π»ΡΡΠ΅ΡΠ½Π°ΡΠΈΠ²Ρ. Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΡΠ°ΡΡΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΡ
Π±Π°Π·ΠΎΠ²ΡΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΠΏΡΠΎΡΠ΅Π΄ΡΡΠ° ΡΠΎΡΠΌΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π°Π½Π°Π»ΠΈΠ·Π° Π°Π»ΡΡΠ΅ΡΠ½Π°ΡΠΈΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. ΠΠ° ΠΏΡΠ΅Π΄ΠΏΡΠΎΠ΅ΠΊΡΠ½ΠΎΠΉ ΡΡΠ°Π΄ΠΈΠΈ ΠΏΡΠΈΡ
ΠΎΠ΄ΠΈΡΡΡ Π΄Π΅ΠΉΡΡΠ²ΠΎΠ²Π°ΡΡ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΠΎΠΉ ΠΈ Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ, ΡΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π² ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠΌ Π² ΡΠΊΡΠΏΠ΅ΡΡΠ½ΠΎΠΌ ΠΎΠΏΡΡΠ΅. ΠΠ»Ρ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π·Π°Π΄Π°ΡΠΈ ΠΎΡΠΎΠ±ΡΠ°Π½Ρ ΡΠ΅ΡΡΡ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π² Π΄Π»Ρ ΡΠΊΡΠΏΠ΅ΡΡΠ½ΡΡ
ΠΎΡΠ΅Π½ΠΎΠΊ. ΠΡ
ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠ° ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π° Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΌΠ½ΠΎΠ³ΠΎΠΊΡΠΈΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π²ΡΠ±ΠΎΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π½Π΅ΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ½ΠΎΠ³ΠΎΠΊΡΠΈΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° Π²Π°ΡΠΈΠ°Π½ΡΠΎΠ², ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΡ
ΡΠΎΡΠΌΠ°Π»ΠΈΠ·ΠΎΠ²Π°ΡΡ Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ°ΡΡΡΠΆΠ΄Π΅Π½ΠΈΡ Ρ ΡΠ°ΡΠΏΠ»ΡΠ²ΡΠ°ΡΡΠΌΠΈ ΠΈΠ»ΠΈ Π½Π΅ΡΠΎΡΠ½ΡΠΌΠΈ ΡΡΠ²Π΅ΡΠΆΠ΄Π΅Π½ΠΈΡΠΌΠΈ. ΠΠΎΡΠΊΠΎΠ»ΡΠΊΡ Π² ΡΠ°ΠΊΠΈΡ
ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΎΡΡΡΡΡΡΠ²ΡΠ΅Ρ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΠΉ Π΄Π»Ρ ΠΊΠΎΠ½ΡΡΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ² Π½Π°Π±ΠΎΡ ΠΈΠ·ΠΌΠ΅ΡΠΈΠΌΡΡ
ΡΠ²ΠΎΠΉΡΡΠ², ΡΡΠΏΠ΅ΡΠ½ΠΎ Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π° ΡΠΎΡΠΌΠ°Π»ΠΈΠ·Π°ΡΠΈΡ Π»ΠΈΠ½Π³Π²ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠ΅Π½ΠΎΠΊ ΠΈΠ½ΡΡΠΈΡΠΈΠ²Π½ΡΡ
ΠΈΠ»ΠΈ Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΏΠ°ΡΠ½ΡΡ
ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΉ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΡ
Π΅ΠΌΡ ΠΠ΅Π»Π»ΠΌΠ°Π½Π° - ΠΠ°Π΄Π΅, ΡΠΊΠ°Π»Ρ Π‘Π°Π°ΡΠΈ ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΡΡΠ½ΠΊΡΠΈΠΉ ΠΏΡΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ½ΠΎΡΡΠΈ. ΠΡΠΊΠΎΠΌΠΎΠ΅ Π½Π΅ΡΠ΅ΡΠΊΠΎΠ΅ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²ΠΎ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΎ Π½Π°Ρ
ΠΎΠΆΠ΄Π΅Π½ΠΈΠ΅ΠΌ ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ Π²Π΅ΠΊΡΠΎΡΠ° ΠΈ Π½Π°ΠΈΠ±ΠΎΠ»ΡΡΠ΅Π³ΠΎ ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠΈΡΠ»Π° Π΄Π»Ρ ΠΌΠ°ΡΡΠΈΡΡ ΠΏΠΎΠΏΠ°ΡΠ½ΡΡ
ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΉ. ΠΠΎΠ³ΠΈΠΊΠ° Π²ΡΠ±ΠΎΡΠ° Π²Π°ΡΠΈΠ°Π½ΡΠ° ΡΡΡΠΎΠΈΡΡΡ ΠΏΠΎ ΠΌΠ°ΠΊΡΠΈΠΌΠΈΠ½Π½ΠΎΠΌΡ ΠΊΡΠΈΡΠ΅ΡΠΈΡ, Π΄ΠΎΠΏΠΎΠ»Π½Π΅Π½Π½ΠΎΠΌΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΌΠ°ΡΡΠΈΡΡ ΡΡΡΡΠΏΠΎΠΊ, ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡΠΈΠΌ ΡΠ°Π·Π»ΠΈΡΠΈΡΡ Π°Π»ΡΡΠ΅ΡΠ½Π°ΡΠΈΠ²Ρ ΠΏΡΠΈ ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠΈ ΠΎΠ΄ΠΈΠ½Π°ΠΊΠΎΠ²ΡΡ
ΠΈΠ»ΠΈ Π±Π»ΠΈΠ·ΠΊΠΈΡ
ΠΈΡ
ΠΎΡΠ΅Π½ΠΎΠΊ. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²ΡΡΠ²Π»Π΅Π½Π° ΠΏΡΠΈΠΎΡΠΈΡΠ΅ΡΠ½ΠΎΡΡΡ Π΄ΠΈΠ²Π΅ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ
ΡΠ½Π΅ΡΠ³ΠΎΠ½ΠΎΡΠΈΡΠ΅Π»Π΅ΠΉ Π΄Π»Ρ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ ΠΏΠΎΠ»Π΅Π·Π½ΠΎΠΉ ΡΠ½Π΅ΡΠ³ΠΈΠ΅ΠΉ ΠΏΠΎΡΡΠ΅Π±ΠΈΡΠ΅Π»Π΅ΠΉ Π―ΠΌΠ°Π»Π°. Π’Π°ΠΊΠΈΠΌ Π΄ΠΈΠ²Π΅ΡΡΠΈΡΠΈΡΠΈΡΡΡΡΠΈΠΌ Π²ΡΠ±ΠΎΡΠΎΠΌ ΡΠ½Π΅ΡΠ³ΠΎΠΈΡΡΠΎΡΠ½ΠΈΠΊΠ°, ΡΠΎΠ³Π»Π°ΡΠ½ΠΎ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠΌΡ ΠΌΠΎΠ΄Π΅Π»ΡΠ½ΠΎΠΌΡ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡ, ΠΎΠΊΠ°Π·Π°Π»ΠΎΡΡ ΠΏΡΠ΅Π΄ΠΏΠΎΡΡΠ΅Π½ΠΈΠ΅ Π°ΡΠΎΠΌΠ½ΠΎΠΉ ΡΠ½Π΅ΡΠ³ΠΈΠΈ. ΠΠ° Π²ΡΠΎΡΠΎΠΌ ΠΌΠ΅ΡΡΠ΅ ΠΏΠΎ ΠΏΡΠ΅Π΄ΠΏΠΎΡΡΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ - Π³Π°Π·ΠΎΡΡΡΠ±ΠΈΠ½Π½ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ ΠΎΠΏΠ΅ΡΠ΅ΠΆΠ°ΡΡΠΈΠ΅ Π²Π΅ΡΡΠΎΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ. ΠΠ°ΠΌΡΠΊΠ°ΡΡ ΡΡΠ΄ ΠΏΠΎ ΠΏΡΠ΅Π΄ΠΏΠΎΡΡΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π΄ΠΈΠ·Π΅Π»Ρ-Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡΠ½ΡΠ΅ ΡΡΡΠ°Π½ΠΎΠ²ΠΊΠΈ. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π² Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ΅Π΄Π΅ Ρ
ΠΎΡΠΎΡΠΎ ΠΊΠΎΡΡΠ΅ΡΠΏΠΎΠ½Π΄ΠΈΡΡΡΡΡΡ Ρ ΠΎΠ±ΡΡΡΠ½ΡΡΡΠΈΠΌΠΈ ΡΠ°ΠΊΡΠΎΡΠ°ΠΌΠΈ Π²ΡΠ±ΠΎΡΠ°. ΠΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Π° Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ² Ρ ΠΏΡΠ΅ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π»ΠΈΠ½Π³Π²ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠ΅Π½ΠΎΠΊ Π² ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅ Π² ΠΌΠΎΠ΄Π΅Π»ΡΠ½ΠΎ-ΠΌΠ΅ΡΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°ΠΏΠΏΠ°ΡΠ°Ρ ΠΌΠ½ΠΎΠ³ΠΎΠΊΡΠΈΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π²ΡΠ±ΠΎΡΠ° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎ ΠΈ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π²Π°ΡΠΈΠ°Π½ΡΠΎΠ². Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°Π±ΠΎΡΡ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΏΡΠΈ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ΅ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΡΡ
ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΉ ΠΈ ΡΡ
Π΅ΠΌ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΠΎΡΡΠ°ΡΠ»ΠΈ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΈ Π΅Π΅ ΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΡ Π΄Π»Ρ ΡΠ΄Π°Π»Π΅Π½Π½ΡΡ
Π°ΡΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ.Provision of useful energy is the most important condition for realising the potential of underdeveloped regions. For new development areas, including the Yamal Peninsula, there are various energy alternatives. Based on well-known basic approaches, the article presents a procedure for formalising the analysis of alternatives mostly using qualitative initial data. At the pre-project stage, only limited and fuzzy information (predominantly in the form of expert opinions) is accessible. To achieve the set goal, six criteria for export assessment were selected and further processed using fuzzy multicriteria decision-making models based on fuzzy multicriteria analysis of alternatives in order to formalise logical reasoning with vague or imprecise statements. Due to insufficient measurements for constructing fuzzy sets, linguistic estimates of intuitive or logical pairwise comparisons were formalised using the Bellman-Zadeh model, the Saaty scale and the construction of membership functions. The fuzzy set was obtained by finding the eigenvector and the largest eigenvalue for the pairwise comparison matrix. Implementation of the maximin criterion along with the concession matrix allowed us to distinguish between alternatives when obtaining the same or similar estimates. As a result, the study showed the priority of diversification of primary energy source to provide useful energy to consumers in Yamal. According to the model, the most preferable source is atomic energy. In second place are gas turbine technologies, which are significantly ahead of wind energy sources. Diesel generators are considered the least favourable. Thus, the results of fuzzy modelling correspond with the explanatory factors of choice. The fuzzy set method with the transformation of linguistic estimates into quantitative ones can also be included in the apparatus of multicriteria selection with respect to combined options. The research findings can be used to prepare comprehensive strategies and schemes for location of industries and the energy infrastructure in remote Arctic territories.Π Π°Π±ΠΎΡΠ° Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π° ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΏΠ»Π°Π½ΠΎΠΌ Π½Π°ΡΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΠ½ΡΡΠΈΡΡΡΠ° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π£ΡΠ Π ΠΠ Π½Π° 2022 Π³ΠΎΠ΄.The article has been prepared in accordance with the plan of the Institute of Economics of the Ural Branch of RAS for 2022
Siliceous microfossil distribution in the surficial sediments of Lake Baikal
Examination of surficial sediments at 16 stations shows minor, but consistent differences in the numbers and kinds of siliceous microfossils deposited in different regions of Lake Baikal. There is a general north-south decreasing trend in total microfossil abundance on a weight basis. Endemic plankton diatom species are the most abundant component of assemblages at all stations. Chrysophyte cysts are present at all stations, but most forms are more abundant at northern stations. Non-endemic plankton diatom species are most abundant at southern stations. Small numbers of benthic diatoms and sponge spicules are found in all samples. Although low numbers are present in offshore sediments, the benthic diatom flora is very diverse. Principal components analysis confirms primary north-south abundance trends and suggests further differentiation by station location and depth.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43071/1/10933_2004_Article_BF00682594.pd
Modelling the Heterogeneity of the Mutual Influence between Russian Regions in the Manufacturing Industry
ΠΠ°ΠΆΠ½ΡΠΌ Π°ΡΠΏΠ΅ΠΊΡΠΎΠΌ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΡΠ²Π»ΡΠ΅ΡΡΡ Π°Π½Π°Π»ΠΈΠ· ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ
Π½Π° ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠ΅ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ. Π ΡΠ²ΡΠ·ΠΈ Ρ ΡΡΠΈΠΌ ΠΏΡΠΈΠΎΠ±ΡΠ΅ΡΠ°Π΅Ρ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΡΠΎΠ³ΠΎ Π²Π»ΠΈΡΠ½ΠΈΡ. Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΈ ΠΎΡΠΈΠ³ΠΈΠ½Π°Π»ΡΠ½ΡΠΉ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠΉ Π΄Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ
Π½Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΠ΅ ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠ΅ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Π‘Π²Π΅ΡΠ΄Π»ΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ Ρ ΠΎΡΡΠ°Π»ΡΠ½ΡΠΌΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠ°ΠΌΠΈ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ Π³ΠΈΠΏΠΎΡΠ΅Π·ΠΎΠΉ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠ΅Π΄ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅, ΡΡΠΎ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ ΠΌΠ°ΡΡΠΈΡΡ ΠΌΠ΅ΠΆΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΠΉ ΡΠ²Π»ΡΡΡΡΡ ΠΏΡΠΎΠΊΡΠΈ-ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΠΈ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠΌΠΈ ΡΡΠ΅ΠΏΠ΅Π½Ρ ΡΡΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΡ. ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΠΎΡΡΡ Π΄Π°Π½Π½ΠΎΠΉ Π³ΠΈΠΏΠΎΡΠ΅Π·Ρ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Π° ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ Π°Π½Π°Π»ΠΈΠ·ΠΎΠΌ Π½Π°Π»ΠΈΡΠΈΡ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Π΅ΠΉ ΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π΅Π½Π½ΡΡ
ΡΠ΅ΠΏΠΎΡΠ΅ΠΊ ΠΌΠ΅ΠΆΠ΄Ρ Π‘Π²Π΅ΡΠ΄Π»ΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΡΡ ΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ Π Π€. ΠΠ° ΠΏΠ΅ΡΠ²ΠΎΠΌ ΡΡΠ°ΠΏΠ΅ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΡΡΡ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΎΠ±ΡΠ΅ΠΌΠ° Π²ΡΠΏΡΡΠΊΠ° Π² ΡΠ΅ΠΊΡΠΎΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ Π‘Π²Π΅ΡΠ΄Π»ΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ ΠΎΡΡΠ°Π»ΡΠ½ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π Π€ Ρ ΡΠ΅Π»ΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ ΡΠΈΠ»Ρ Π²Π·Π°ΠΈΠΌΠΎΠ²Π»ΠΈΡΠ½ΠΈΡ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. ΠΠ° Π²ΡΠΎΡΠΎΠΌ ΡΡΠ°ΠΏΠ΅ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΊΠ²Π°Π½ΡΠΈΠ»ΡΠ½ΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΠΈΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
, ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΡΠΈΡΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ, ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΉ Π½Π° ΠΏΠ΅ΡΠ²ΠΎΠΌ ΡΡΠ°ΠΏΠ΅, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠΉ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Π‘Π²Π΅ΡΠ΄Π»ΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ ΠΎΡΡΠ°Π»ΡΠ½ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π Π€ Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. Π ΡΡΠ°ΡΡΠ΅ Π΄ΠΎΠΊΠ°Π·ΡΠ²Π°Π΅ΡΡΡ ΠΏΡΠ°Π²ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡ ΠΊΠ²Π°Π½ΡΠΈΠ»ΡΠ½ΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΡ ΠΠΠ Π΄Π°Π΅Ρ Π½Π΅ΠΊΠΎΡΡΠ΅ΠΊΡΠ½ΡΠ΅ ΠΎΡΠ΅Π½ΠΊΠΈ Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠ΅ΠΉ ΠΌΠ΅ΠΆΠ΄Ρ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΠΌΠΈ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΠΈ. ΠΡΠΎ Π²ΡΡΠ°ΠΆΠ°Π΅ΡΡΡ Π² ΡΠΎΠΌ, ΡΡΠΎ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΡ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ Π·Π°Π²ΠΈΡΡΡ ΠΎΡ ΡΡΠΎΠ²Π½Ρ q-ΠΊΠ²Π°Π½ΡΠΈΠ»Ρ Π·Π°Π²ΠΈΡΠΈΠΌΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ. ΠΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΡΠΎΠ²Π΅Π½Ρ ΡΠ΅Π½ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
Π½Π΅ ΠΎΠΊΠ°Π·ΡΠ²Π°Π΅Ρ Π²Π»ΠΈΡΠ½ΠΈΡ Π½Π° ΠΈΡ
Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ΅ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΡΠΎ Π‘Π²Π΅ΡΠ΄Π»ΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΡΡ. Π’Π°ΠΊΠΆΠ΅ ΡΠ»Π΅Π΄ΡΠ΅Ρ ΠΎΡΠΌΠ΅ΡΠΈΡΡ, ΡΡΠΎ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ Π·Π½Π°Π½ΠΈΠΉ ΡΠ²Π»ΡΠ΅ΡΡΡ Π΄ΡΠ°ΠΉΠ²Π΅ΡΠΎΠΌ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π² ΡΡΠ΅ΡΠ΅ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠ΅ΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°Π±ΠΎΡΡ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΏΡΠΈ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ΅ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΉ, ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ ΠΈ ΡΡ
Π΅ΠΌ ΡΠ°Π·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΎΡΡΠ°ΡΠ»Π΅ΠΉ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»Π° ΡΠ°Π·Π²ΠΈΡΠΈΡ Π‘Π²Π΅ΡΠ΄Π»ΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ Ρ ΠΎΡΡΠ°Π»ΡΠ½ΡΠΌΠΈ ΡΡΠ±ΡΠ΅ΠΊΡΠ°ΠΌΠΈ Π Π€.As factors affecting interregional interactions play an important role in regional economic development. Thus, developing a methodology for assessing these interactions is becoming urgent. The article proposes a methodological approach to analyse the factors influencing possible interactions between Sverdlovsk oblast and other constituent entities of the Russian Federation in the manufacturing industry. It is hypothesised that the elements of an interregional interaction matrix are proxy variables characterising the degree of this interaction. An economic analysis of relations and production chains between Sverdlovsk oblast and other constituent entitles confirmed this hypothesis. First, based on the spatial distribution of manufacturing output in the examined regions, values of an indicator showing the strength of their mutual influence were determined. Second, the impact of economic, infrastructural and institutional factors on the obtained indicator, characterising the interaction between Sverdlovsk oblast and other regions, was assessed using quantile regression. In this case, such a technique was chosen instead of the classical ordinary least squares (OLS) regression that incorrectly estimates the dependencies between the studied variables. This is expressed in the fact that the regression coefficients depend on q-quantile of the dependent variable. We have revealed that price levels of the examined regions do not affect their possible interactions with Sverdlovsk oblast. Simultaneously, the dissemination of knowledge acts a driver of interaction between the considered regional manufacturing industries. The research findings can be used to prepare strategies, programmes and schemes for the placement and development of industries, considering the potential of Sverdlovsk oblast and other Russian regions.Π‘ΡΠ°ΡΡΡ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²Π»Π΅Π½Π° Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΡΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Π½ΡΠΌ ΠΏΠ»Π°Π½ΠΎΠΌ ΠΠΠ ΠΠ½ΡΡΠΈΡΡΡΠ° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π£ΡΠ Π ΠΠ.The article has been prepared in accordance with the plan of Institute of Economics of the Ural Branch of RAS for 2021β2023
The βMelosira yearsβ of Lake Baikal: Winter environmental conditions at ice onset predict underβice algal blooms in spring
Winter primary production in seasonally iceβcovered lakes historically has not been well studied, but it is increasingly recognized as an important component of lake metabolism. Lake Baikal in Siberia is not only the World's oldest, deepest, and most biologically diverse lake, but also where large underβice blooms of the diatom Aulacoseira baicalensis (formerly Melosira) occur in some years. The phenomenon of βMelosira yearsβ is noteworthy both for the intensity of the diatom blooms, in which total underβice production can be a majority of total annual production, and for the enigmatic regularity of their occurrence every 3β4 yr. The degree to which these episodic blooms might be controlled by external forcing and endogenous lake processes has been debated for decades. We used a 50βyr time series of phytoplankton observations to statistically model the occurrence of Aulacoseira blooms as a function of meteorological and climatological predictor variables. The results support the hypothesis that a confluence of meteorological conditions in the preceding fall season, which favor clear ice formation with minimal snow cover, also favor Aulacoseira blooms in the following spring. Further, we observe that this confluence of factors is related to relatively strong states of the Siberian High which, while not strictly periodic, do explain a significant fraction of the interannual bloom pattern. Finally, our analyses show that the timing of the peak abundance of A. baicalensis shifted 1.6 months later across the 50βyr time series, corresponding with the delay in iceβon timing that has been associated with climate change
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