This study investigated climate change impacts on watershed parameters as well as on water balance, water temperatures, and ice-cover regime for 2 large lakes in western Russia, Lakes Ladoga and Onego. Parts of the study occurred during a period of pronounced warming and limited ice cover on Lake Ladoga, which precluded winter surveys of the lake. This limitation notwithstanding, the research provides background climatic and hydrological conditions for the joint Russian-Swiss project "Lake Ladoga-Life under the ice." For both Lakes Onego and Ladoga from 1955 to 2017, air temperature, precipitation, and evaporation data all showed increasing trends, and inflow, outflow, and water levels showed no discernible changes from baseline conditions. Thermal and ice conditions of Lake Onego showed greater sensitivity to climatic changes than corresponding conditions for Lake Ladoga because of the latter's significantly smaller volume and lower heat content. The total ice-cover duration for Lake Onego decreased ∼20 days during the observation period. Detailed data analysis also revealed key characteristics of the Shuya River discharge into Petrozavodsk Bay, where a major part of the fieldwork occurred. River discharge into Lakes Ladoga and Onego increased in the winter. These processes collectively can change the hydrochemical conditions, water quality, and habitat.

The objective of the present study is to define mass distribution laws for a bundle of trees using the methods of statistical simulation modeling in order to calculate chokerless skidding tractors lift capacity. For that purpose a statistical simulation model has been developed to generate forest taxation data necessary for complete filling of skidding tractor grapple. The following samples have been obtained from the regions of the European North of Russia based on the model: masses of bundles of trees that can be placed in grapple and values of vertical component of normal load applied to skidding tractor grapple. Minimum values for masses of bundles may vary in the range of 40-87% from the average value. Maximum values may vary in the range of 8-55% from the average value. The difference between the maximum and minimum masses of bundle values increased with increasing the capacity grapple and decreased with increasing the distance from the butt to grapple. We have determined the dependence of bundle mass variation and values of vertical component of normal load applied to skidding tractor grapple on capacity grapple for the regions of the European North of Russia. The studies have allowed determining recommended values for chokerless skidding tractors lift capacity. The analysis of specifications of various models of skidding tractors has shown that clambunk skidders have deficient marginal lift capacity.

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.

Studying of characteristics of the Lake Onega ice regime and investigating of the climate influence on the formation and destruction of the ice cover requires a continuous chronological series of data on the Lake ice coverage. Ice cover is the percentage of the ice area to the total area of the lake. In 1955–1990, calculations of the ice coverage of the Lake were based on the use of the results of airborne ice reconnaissance. On average for this period, from 5 to 15 values were annually obtained, which was not enough for a comprehensive analysis of the ice coverage variability. In this paper, for the frst time, a daily series of values of the ice coverage of the Lake Onega for the period 2000–2018 had been formed basing on the results of a combined analysis of the following satellite data sets: NSIDC, NOAA NESDIS, corrected by data of the satellite MODIS sensor. Values from November to May were grouped from the above data sets without regards for years of observations, and then the regression analysis of these values made possible to create a model (a polynomial of the 8th degree) of the chronological course of the ice coverage during the period of the ice phenomena existence on the Lake Onega. Te coefcient of determination of the model is 0.74, and the error in determining the ice coverage is 21%. Te average dates of the beginning, end, and duration of periods of the formation (from November 25th to January 19th), the destruction (from April 13th to May 17th) of the ice cover, as well as the total freeze-up time (from January 20th to April 12th) on the Lake Onega for the period 2000–2018 was determined. Te period of ice phenomena on the Lake Onega on average lasts for almost half a year (175 days), of which a signifcant part of the time is a complete freeze-up (84 days). It was found that the rate of formation of the ice cover (1.76% per day) on the Lake Onega is 1.65 times smaller than the rate of its destruction (2.90% per day), which approximately corresponds to similar results obtained for the Lake Ladoga (1.5 times).