Dynamic growth model for oak stands in Moscow, Russia

Abstract

The most objective information about the state of Moscow’s forests is provided by long-term observation data on permanent trial plots. Such data makes it possible to identify changes in forest stands under the influence of recreationists, environmental pollution, and climate change. Long-term observational data are particularly valuable in modeling forest stand growth and productivity. The goal of the study is to develop a dynamic model of the growth of oak stands in Moscow based on long-term observation data. The modelling data were obtained from 7 plots of the permanent sample plot network established by the Forest Experimental Station of the Russian State Agrarian University – Moscow Timiryazev Agricultural Academy. There are a total of 42 inventories and the number of inventories per plot range from 3 to 9. Inventories were carried out between 1927 and 2009. We used three initial state variables for prediction, as in many studies. Taking into account the peculiarities of the inventory of forest stands in Russia, the mean height, quadratic mean diameter and number of trees per hectare were used as initial variables. All obtained models meet the requirements for forest inventory in Russia in terms of error values of stand attributes. The model in this study provides a simple and reliable system for predicting the growth and yield of Moscow oak stands.