<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

Analysis of natural-production conditions for timber harvesting in European North of Russia

Northern Water Problems Institute of the Karelian Research Centre of the Russian Academy of Sciences

Central European Forestry Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Natural-production conditions determine operational efficiency of logging machines. This influence needs to be taken into account at different levels of forest...

Analysis of natural-production conditions for timber harvesting in European North of Russia

Published Online: May 09, 2019

Page range: 81 - 91

DOI: https://doi.org/10.2478/forj-2019-0006

Keywords
natural-production conditions, tree size, relief, soil conditions, timber volume, forest species composition, logging machines, cluster analysis

© 2019 Ilya Shegelman et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Analysis of natural-production conditions for timber harvesting in European North of Russia

Published Online: May 09, 2019

Page range: 81 - 91

DOI: https://doi.org/10.2478/forj-2019-0006

Keywordsnatural-production conditions, tree size, relief, soil conditions, timber volume, forest species composition, logging machines, cluster analysis

© 2019 Ilya Shegelman et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
natural-production conditions, tree size, relief, soil conditions, timber volume, forest species composition, logging machines, cluster analysis