Feedback Modelling of Natural Stand and Plantation Biomass to Changes in Climatic Factors (Temperatures and Precipitation): A Special Case for Two-needles Pines in Eurasia
Abstract: A comparative discussion on advantages and disadvantages of natural stands and plantations, including their productivity and resistance, began from the moment of first forest plantings and continues to this day. In the context, progressive replacement of natural forests by plantations, the question of how that will change the carbon storage capacity of forest cover when replacing natural forests with planted ones in a changing climate becomes extremely relevant. This article presents the first attempt to answer this question at the transcontinental level on a special case for two-needles pine trees (subgenus Pinus L.). The research was carried out using the database compiled by the authors on the tree biomass allocation structure for major tree species of Eurasia, in particular, the 1880 and 1967 data of naturally regenerated and planted sample pine trees, respectively. Multi-factor regression models were calculated after combining the matrix of initial data on the structure of tree biomass with the mean temperature of January and mean annual precipitation; their adequacy indices allow us to consider them reproducible. It is found that the aboveground biomass of equal-sized and equal-aged natural and planted trees increases with the rise in the temperature in the month of January and annual precipitation. This pattern is only partially valid for the branches’ biomass. Iit has a specific character for the foliage one. The biomass of all components of planted trees is higher than that of natural trees, but the percentage excess varies among different components and depends on the level of January’s temperature, but does not depend at all on the level of annual precipitation. The uncertainties of estimations, as well as the nature of the obtained regularities, are discussed in the text.
Keywords: Two-needles pine trees, Natural stands and plantations, Regression models, Biomass equations, Mean January temperature, Annual precipitation