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News
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Зависимость запасов древесины в лесах России от климатических параметров

Лесоведение. 2019. № 2. С. 83–92.
Грабовский В., Zamolodchikov D.

Mean timber storages across different species and age groups of forests based on the State Forest Inventory 2013 data were correlated by means of regression analysis to climatic variables, averaged over 1981–2000. The following species categories were predefined: all species, conifers, hardwoods, softwoods, and others. The following age groups were predefined: all ages, young growth, middle-aged, pre-mature, mature, and oldgrowth forests. Finally, the correlation and regression analyses were undertaken for each of the 20 age and species groups of forests. Mean annual temperature, difference of mean July and mean January temperatures, and annual precipitation were independent variables. Mean timber storages positively correlate to the mean annual temperature and humidity, and negatively correlate with the difference of mean July and mean January temperature. Coefficient of correlation between the mean storages and the mean annual temperature had pronounced growing trend across the species groups, as follows by value: other species, conifers, hardwoods, softwoods. Multiple polynomial regression equations were found for every species and age group. They had all possible linear and squared couplings between independent variables. Coefficients of determination had the highest values (R2 > 0.7) for all forests combined, for hardwood species, and also for mature and middle-aged forests of all species combined and hardwood species. Other forest species and all young-growth forests were the least predictable (R2 < 0.5). The regression equations could be used to forecast changes in the mean storages of timber under changing climate for all forests combined and forests of different age and specie composition.

Research target: Agriculture, Forestry, and Fisheries
Priority areas: engineering science
Language: Russian
DOI
Keywords: статистический анализ statistical analysisgrowing stocksclimate parametersзапасы древесиныклиматические характеристики
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