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Siberian Journal of Forest Science

2021 year, number 2

PREDICTING STEM BIOMASS OF PINE TREES IN NATURAL AND PLANTED FORESTS DUE TO CLIMATE CHANGE

V. A. Usoltsev1,2, I. S. Tsepordey1
1Botanical Garden, Russian Academy of Sciences, Ural Branch, Yekaterinburg, Russian Federation
2Ural State Forest Engineering University, Yekaterinburg, Russian Federation
Keywords: two-needled pines, related equations, average January temperature, average annual precipitation

Abstract

In the context of intensive replacement of natural forests by plantations, it is important to know how this replacement will affect the productivity of forests and their ability to mitigate the effects of climate change. The aim of our study was to establish: (1) how the ratio of biomass and volume of tree stems of two-needled pines (subgenus Pinus L.) of natural and artificial origin changes in temperature and precipitation gradients in Eurasia and (2) what contribution to the explanation of the variability of stem biomass is made by the tree’s forest inventory indices (stem age, diameter and volume), the origin of a stand (natural or artificial) and climatic factors (temperature and precipitation). To achieve this goal, a database of harvest data on the biomass of pine stems in the amount of 975 and 508 in natural and planted stands respectively, was formed. A positive relationship between the stem biomass and the average January temperature in conditions of sufficient moisture and its absence in dry conditions was established. The positive relation of stem biomass to precipitation in cold regions disappears as the transition to warm ones takes place. The stem biomass at the age of maturity in plantations is 15 % higher than in natural stands, and in young stands, on the contrary, it is less by 4 %. The contribution of inventory indices, the origin of stands and climatic factors to the explanation of stem biomass variability was 72, 10 and 18 %, respectively. The results obtained, tested on other tree species, can be useful in selecting tree species that are most tolerant to climate change.