Pinus tabulaeformis growth prediction method

Abstract

The invention discloses a pinus tabulaeformis growth prediction method. Wood growth amount data is analyzed through the Chinese pine; the growth process of the Chinese pine is divided into three stages, namely a slow growth stage, a vigorous growth stage and a growth stopping stage. A pinus tabulaeformis ultimate growth model and a successive year growth model are established, the tree age of thepinus tabulaeformis before 100 years is a slow growth period, the tree age of the pinus tabulaeformis between 101 years and 150 years is a vigorous growth period, and the tree age of the pinus tabulaeformis greater than 150 years is a growth stopping period.

Description

[0001] 1. Technical field [0002] A growth prediction method of Chinese pine, which divides the growth process of Chinese pine into three stages: the slow growth period, the vigorous growth period and the growth stop period by analyzing the wood growth data of Chinese pine, and establishes the limit growth model of Chinese pine and successive years Growth model, in which, the age of Pinus tabulaeformis before 100 years is a period of slow growth, the age of trees between 101 and 150 years is a period of vigorous growth, and the age of trees older than 150 years is a period of growth tending to stop. [0003] 2. Technical background [0004] The growth of forest trees reflects the comprehensive reflection of the adaptation degree of a certain tree species to the site conditions and the effect of management measures. The volume table method is generally used for the growth prediction of Chinese pine. However, in the actual use process, the traditional volume table has obvious sho...

AI Technical Summary

Problems solved by technology

[0005] ①The traditional volume table data is old, and the regional restrictions are too strong, so it is impossible to accurately predict and invert all regions;

[0006] ②The traditional volume table cannot be adjusted according to the specific site information, resulting in large deviations in the estimated data;

[0007] ③The volume table can only estimate the volume, but cannot reflect the growth of tree height and DBH over time, and cannot predict the growth of trees

[0008] Therefore, in the process of forecasting Pinus tabulaeformis, the traditional volume table method has relatively large defects, and it is impossible to predict the annual growth of tree height diameter at breast height.