The article analyzes the development of voluntary forest certification by the Forest Stewardship Council (FSC) system in Russia. The article is based on the review of diverse information sources, analysis of the reports of timber processing enterprises, personal observations during certification audits, discussions in workgroups, and information collected at training courses. We evaluated the present state of voluntary forest certification in Russia, analyzed non-compliances of the activity of Russian wood processing enterprises with the national standard FSC-STD-RUS-V6-1-2012 and indicated possible reasons for non-fulfillment of the requirements. We also presented problems in the development of forest certification in Russia and possible ways for its further development. By the end of 2015, about 40 million hectares were certified, approximately 160 certificates were issued on forest management and 440 certificates on chain of custody. The 6th principle of the national forest management standard is the most problematic for logging enterprises. The principle concerns the requirements on the evaluation of impact of enterprise's activity on the environment. About 40% of non-compliances identified by auditors referred to the indicators of the 6 th principle. We argue that the main problems of forest certification development in Russia are contradictions between the principles and the criteria of FSC and the requirements of Russian forest legislation, retention of biodiversity and high conservation value forests, lack of economic incentives for introduction and implementation of certification requirements, and high cost of audits. Despite the existing problems, the certification remains one of the most important instruments for achieving sustainable forest management in Russia.
The effectiveness of harvesting machines, their reliability, and the level of negative environmental impact depends on the degree of adaptation of the equipment to natural-production conditions (NPC). To choose the equipment it is necessary to allocate groups of areas with close NPC. The purpose of the study is to form methodological tools for forest industry typification of forest areas by NPC. It is proposed to carry out the typification of forest areas based on cluster analysis. For this purpose, a methodology has been developed, including: setting the goal of typing areas by NPC; data collection on NPC; conducting cluster analysis; decision making on typification of areas by NPC. The task of cluster analysis is to divide, on the basis of a certain set of data, the set of forest areas into groups with similar NPCs. It is proposed to use Euclidean distances as a measure of belonging to one of the groups, and to determine the data set by indicators describing the NPC. The proposed methodology has been tested on the example of the European North of Russia (ENR). The study showed that three zones can be distinguished in ENR: zone A, including the Murmansk region; zone B, including the Republic of Karelia, the Republic of Komi and the Arkhangelsk region; zone C, including the Vologda region. Additionally, two subzones are distinguished in zone B: the West Karelian Upland and the territories belonging to the Northern, Subpolar and Polar Urals. The proposed methodology allows to increase the degree of formalization and convenience of the typification process of forest areas by NPC, to take into account a wide range of various aspects of natural-production conditions, their probabilistic nature, as well as to flexibly carry out the typification of areas for specific purposes. The research results may be applicable in solving problems of searching for effective technologies and rational parameters of logging machine systems.
Natural-production conditions determine operational efficiency of logging machines. This influence needs to be taken into account at different levels of forest management. It is necessary to allocate areas with similar natural-production conditions for effective forest management. It allows simplifying the decision making process for selecting logging technology and machines. The purpose of this study was to establish areas with similar natural and production conditions in the European North of Russia (ENR). In addition, for small enterprises, we recommend logging technologies and logging machines that can be used in established areas. We determined the indicators of the natural-production conditions of ENR regions and compared them. Cluster analysis was used to compare the indicators. We found that ENR can be divided into three main zones A, B, C and two subzones B1 and B2 with similar natural-production conditions. In the zones A, B and the subzones B1 and B2, small logging enterprises should use a harvester and a forwarder. In the zone C, the enterprises can use a logging system including a harvester and a forwarder or a logging system including a feller buncher, a skidder and a processor. The logging system should be based on the light class of logging machines for the zone A, the medium class or the heavy class for the zones B, C and the subzones B1, B2, the heavy class of machines for the zone C.
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