A comprehensive evaluation of forest value based on carbon sequestration stock prediction

Abstract

The increasing greenhouse effect globally, the excessive deforestation of forests and the weakening of forest carbon storage capacity have brought about drastic changes in the global climate and posed a great threat to the biosphere. Therefore, the issue of "making efficient use of forest carbon storage capacity and diversified value of forests" has attracted our attention. To better analyze the problem of carbon sequestration and forest value and formulate a reasonable forest management plan, this article established two models: the "grey system model" and "BP neural network prediction model." The two models used China's forest inventory data in the past 40 years to predict that the average value of total forest carbon sequestration in China in a hundred years is 189.37×108t. Aiming at the problem of forest value evaluation, this article apply "grey correlation analysis method," "main component analysis model," and "fuzzy comprehensive evaluation model." This article considers the value of forests from two aspects: ecological value and economic value. In terms of ecological value: this article found that forests have various values such as "carbon sequestration, water conservation, soil conservation, and biodiversity maintenance"; Most forests have a "U-shaped transition period" in carbon sequestration capacity. "Tree age and tree composition structure" are the main factors affecting carbon sequestration capacity. In terms of economic value, this article found that "increasing the proportion of young trees and suitable for the production of forest products" is a good way to increase the economic value of forests. In addition, the research shows that there are obvious differences in the degree of carbon sequestration capacity and economic value of forests in different climate areas such as "subtropical zone, warm temperate zone, and middle temperate zone.".