Phytosociological evaluation of terrestrial habitat types in Pyramiden area (Svalbard, Norway)

Natural habitats in the area of Pyramiden town (Svalbard, Norway) were assessed as a part of landscape planning for purposes of tourism development. Habitat types evalu-ation was done by using phytosociological units and assessed by IUCN categories. Altogether, 15 main habitat types were united in following groups: 1. Arctic tundra, 2. Barrens, screes, young alluvia areas and glaciers, 4. Wetlands and marshes, 5. Meadows and grasslands, 6. Anthropogenic open plant communities

A process-based approach to management of the enterprise

Establishing an efficient management system is an especially pressing issue for machinery industry as a basic sector of economy in a country. The present paper considers establishing a management system oriented towards increasing enterprise value and customer satisfaction through the integration of process-based management and a Balanced Scorecard. An integrated management system enables structuring of organization processes, redesigning them with regard to external changes as well as applying a balanced scorecard connecting functional units by means of defining strategic objectives and measurable indicators detailing and controlling these objectives and thus increasing the efficiency of processes orienting an organization towards a customer

The Role of White-rot Fungi in Herbicide Transformation

Understanding herbicide transformation is necessary for pesticide development for their safe and efficient use, as well as for developing pesticide bioremediation strategies for contaminated soil and water. Recent studies persuasively demonstrated the key role of soil white-rot fungi in biotransformation of various anthropogenic environmental contaminants. However, often this common knowledge is not associated with specific metabolic processes of fungi and therefore cannot be transformed into specific recommendations for agricultural practice. The given review offers a systematic collection and analysis of the current knowledge about herbicide transformation by white-rot fungi at the cellular and molecular levels. Special attention is given to the role of oxidative enzymes such as laccases, lignin peroxidases, and manganese peroxidases in the biotransformation processes

Determinants of Tax Capacity for a Territory (The Case of the Russian Federal Districts)

In this article, the tax capacity of the territories in the Russian Federation was studied. The study was conducted based on the aggregation for eight federal districts, including data on 85 subjects of the Russian Federation from 2009–2018. To determine the factors that have the strongest impact on tax capacity at the subnational level, an econometric analysis of the panel data was performed using the Stata program. In the development of the model, tax share was used as the resulting indicator. The article analyzes the impact on tax share of 16 macroeconomic indicators that reflect the human and financial potential of taxpayers in a federal district, the investment attractiveness and innovative activity of the territory, as well as global financial and economic regulators. The hypothesis that due to significant differences in the socioeconomic development of territories, the determinants of tax capacity will differ by federal districts, was confirmed. However, it was proved that such differences are not related to the specific features of socioeconomic development inherent in the constituent entities of the Russian Federation. Among the selected factors in pooled regression, fixed effects, and random effects models, the level of employment of the population and the financial results of companies were considered the most significant. The significance of the level of employment of the population could be determined by a clear deficit in gross fixed capital accumulation against the background of a high degree of depreciation of fixed assets and the share of manual labor

Protected areas network in the Murmansk Region: yesterday, today, and tomorrow

The article represents a retrospective of nature conservation in the Murmansk Region. It is devoted to the period since the first State Nature Reserves to the present day. Today, the network of Protected Areas (PA) in the Murmansk Region consists of three nature state Reserves, one National Park, two nat-ural parks, 12 protected areas “Zakaznik”, 55 nature monuments and the protected area of the Polar-Alpine Botanical Garden-Institute. The total area of the PA is 1,947,799.4 hectares or 13.4% of the Mur-mansk Region. An effectiveness of the PA was assessed due to the correspondence of the protection regimes and the threats. The authors concluded that effective environmental protection could be realized only in small part of PA, mainly in nature state reserves and national park, whose total area is only 4.2% of the Murmansk Region. At the present level of efficiency, even if it will be possible to achieve a share of Pas equal to 16.4% of the region’s area, it is hardly possible to guarantee the proper level of biodiversity conservation and the stability of the ecosystem of the region

Current and past climate co‐shape community‐level plant species richness in the Western Siberian Arctic

The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. This study assesses, models, and maps the geographic patterns of community‐level plant species richness in the Western Siberian Arctic and estimates the relative impact of environmental and anthropogenic factors driving these patterns. With our study, we aim at contributing toward conservation efforts for Arctic plant diversity in the Western Siberian Arctic. We investigated the relative importance of environmental and anthropogenic predictors of community‐level plant species richness in the Western Siberian Arctic using macroecological models trained with an extensive geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non‐vascular plants substantially contribute to species richness and ecosystem functions in the Arctic. We found that the mean community‐level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South‐West to North‐East, which can be well explained by environmental factors. We found that paleoclimatic factors exhibit higher explained deviance compared to contemporary climate predictors, potentially indicating a lasting impact of ancient climate on tundra plant species richness. We also show that the existing protected areas cover only a small fraction of the regions with highest species richness. Our results reveal complex spatial patterns of community‐level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary. We suggest that while community‐level plant species richness is mostly driven by environmental factors, an improved spatial sampling will be needed to robustly and more precisely assess the impact of human activities on community‐level species richness patterns. Our approach and results can be used to design conservation strategies and to investigate drivers of plant species richness in other arctic regions

Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels

Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels