The ecological indicator values are the most common and sufficiently effective method of habitat assessment. The aim of our research review is to analyze current studies from 2020 to 2022 in which researchers have used Ellenberg indicator values to address a variety of problems. We limited the study to papers that are published in journals indexed by Scopus and Web of Science. The total number of records examined was 358. The number of records selected was 98. Visualization of the distribution of studies by country is based on the GeoCharts library. The results revealed that about half of the studies were conducted in Germany and Poland, and the most common objects were forests and grasslands. Almost half of the studies were devoted to ecological niches, habitat analysis, assessment of vegetation dynamics, and influence of various factors on plants. The analyzed articles are actively cited. In general, our research analysis revealed the effectiveness of Ellenberg indicator values for solving a wide range of urgent problems for a variety of plant communities, and different climate zones. The results of our research confirmed the advisability of actively using this approach.

The conservation of biodiversity and ecosystem sustainability is essential for human well-being. An important tool for addressing this issue is ecological indicators. This overview document examines recent studies covering the period 2018–2022 that use the values of the Landolt indicator as one of the analysis methods. The total number of records examined was 8910. After excluding irrelevant, inconsistent and duplicate records, 91 records were selected. The selection criteria were the presence of the English abstract and a digital object identifier (DOI). We chose the VOSviewer software for data analysis and visualization. The analysis of research geography, types of plant communities under research, research topics, the network of co-authorship and relationship papers, as well as the publication activity and citation rate of the authors, is carried out. The results revealed that the geography of using Landolt indicator values is quite wide, while they are more often used in Switzerland, Italy and Russia. The most important and frequently cited studies were carried out in the context of large international projects, confirming the importance of scientific cooperation in the development of environmental indicators. The Landolt indicator values showed effectiveness in the study of forests, bogs, riparian vegetation, a coarse quarry waste dump, and in assessing the urban environment. At the same time, the vegetation dynamics and influence of various factors on plants were studied most often. It was revealed that Landolt indicator values can serve as an effective universal method that integrates many aspects of the environment and allows for a comprehensive multicriteria analysis of environmental factors, habitat stability, vegetation diversity and dynamics for different plant communities at different spatial scales over a wide geographical area. This is confirmed by the high citation rate of the papers. We recommend the Landolt indicator values for a wider use, including in the monitoring of ecosystems and individual species for their conservation and sustainable management. In order to achieve this goal, it is necessary to extend the network of relationships between the authors, which is not very well developed at the moment. The research results obtained are useful for the further successful development not only of the Landolt indicator values but also of environmental indicators in general.

Forest typology holds the central position in modern forestry. We give an overview of research on forest typology in Russia. Forest typology in Russia actively developed and improved with respect to requests forestry throughout the entire period of its existence. It remains the necessary basis for preserving the biodiversity of land ecosystems and ensuring sustainable forest management amid the growing anthropogenic impact and climate change. The birth of scientific forest typology is associated with the name of G.F. Morozov. A biogeocoenotic approach to forest classification was offered by V.N. Sukachev. V.N. Sukachev developed classifications for boreal forests which had been little affected by economic activity. The biogeocoenotic approach proved effective there. However, when literally applied to commercial forests, the biogeocoenotic approach sometimes failed to deliver satisfying results. The exponential shrinkage of natural forests and the increasing share of dynamic secondary growth brought about the need to reflect the time-related forest changes in classifications. The origins of the genetic approach can be found in the writings of G.F. Morozov. The first satisfactory geo-genetic forest classification was built by B.A. Ivashkevich. B.P. Kolesnikov provided the theoretical grounding and main postulates for the approach. According to B.P. Kolesnikov, a geographical and genetic classification means a classification based on the forest origin and evolution patterns which takes account of all the forest ecosystem stages and can be used to predict their future changes. Currently forest typology develops as an interdisciplinary science. It integrates forestry, geobotanics, forest taxation, soil sciences, biogeography, geology, and landscape ecology. A new methodology is being developed. It is a synthesis of forest ecology and synergetic. It uncovers new reserves for the forest science development.

The iron and steel industry is one of the main industrial contributors to air pollution. The aim of our study is to analyze modern studies on air pollution by the iron and steel industry, as a result of which the geography and research directions and the degree of development of current issues will be assessed, and the most cited articles and journals will be identified. A review of contemporary research (2018–2024) was conducted on the basis of articles with a digital object identifier (DOI) using machine learning methodologies (VOSviewer software version 1.6.20). The number of articles selected was 80. The heat map of study density clearly showed that the geographic distribution of studies was extremely uneven. A total of 65% of the studies were conducted in China, 9% in Nigeria, 6% in Russia, 3% in Poland, and 3% in Turkey. The remaining 14% of articles represent a series of single studies conducted in 11 countries. The revealed geographical imbalance between countries with developed production and the number of studies conducted in them shows a significant shortcoming in monitoring research. Most of the studies (20%) were devoted to the assessment of multicomponent emissions. A special place among them was occupied by the inventory of emissions using various methods. The next main directions in terms of the number of articles were aimed at studying the toxic metal emissions (19%), at the analysis of organic emissions (19%), at the modeling and forecasting of emissions (18%), and at particulate matter studies (15%). The main features of the articles for each direction are briefly noted. Citation analysis made it possible to compile a rating of articles of greatest scientific interest and the most authoritative journals. Citation network analysis revealed important insights into the structure of scientific communication in the monitoring of atmospheric pollution from the iron and steel industry. The results of our review will contribute to the consolidation of scientists, the identification of gaps in scientific knowledge, and the improvement of environmental policy and technological solutions.

Understanding the dynamics and system of interrelationships between habitats and plant communities is key to making reliable predictions about sustainable land use, biodiversity conservation and the risks of environmental crises. At the same time, assessing the complex of environmental factors that determine the composition, structure and dynamics of plant communities is usually a long, time-consuming and expensive process. In this respect, the assessment of habitats on the basis of the indicator properties of the plants is of great interest. The aim of our study was to carry out a comprehensive review of vegetation dynamics studies based on the Ellenberg and Landolt indicator values in the last five years (2019–2023). We identified their strengths and priority areas for further research, which will contribute to improving the ecological indicator values for studying vegetation dynamics. The analysis of publications was carried out based on the recommendations of PRISMA 2020 and the VOSviewer software(version 1.6.18). The wide geographical range and high reliability of Landolt and Ellenberg indicator values for the study of different plant communities and variations in their dynamics are demonstrated. At the same time, the application of these environmental indicator values has its peculiarities. For example, the Ellenberg indicator values show a wider research geography and are more often used to study the dynamics of forest ecosystems than the Landolt indicator values, which are more often used to study disturbed landscapes and the dynamics of individual species. However, these methods have been used with almost the same frequency for grasslands, wetlands and coastal vegetation. The citation analysis confirmed the high interest in the environmental indicator values and their widespread use in research, but also revealed the weak development of a network of relationships. This suggests that modern researchers are not well aware of, and rarely use, the results of research carried out in recent years, especially if they are based on indicator values other than those used by them. At the same time, a number of unresolved issues are clearly identified, which require additional research and a consolidation of research teams if they are to be addressed more successfully. We hope that the results of this meta-analysis will provide the impetus for further development of the concept of environmental indicators and help researchers to overcome the current questions around applying indicator values in the study of vegetation dynamics, as well as help researchers to understand the strengths of this methodology.