A Review of Research on Forest Ecosystem Quality Assessment and Prediction Methods

Author:

Guo Ke1234,Wang Bing1234,Niu Xiang234

Affiliation:

1. School of Information Science & Technology, Beijing Forestry University, Beijing 100083, China

2. Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China

3. Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Beijing 100091, China

4. Dagangshan National Key Field Observation and Research Station for Forest Ecosystem, Xinyu 336600, China

Abstract

The accurate assessment and prediction of forest ecosystem quality is an important basis for evaluating the effectiveness of regional ecological protection and restoration, establishing a positive feedback mechanism for forest quality improvement and restoration policies, and promoting the construction of an ecological civilization in China. Based on the existing studies at home and abroad, this paper mainly analyzes and summarizes the connotation of forest ecosystem quality, assessment index systems, assessment and prediction methods, and outlooks on the existing problems of imperfect forest ecological quality assessment index systems, preliminary assessment and prediction capabilities, and unknown dynamic responses of forest ecological quality to climate change, etc. Efforts should be made to develop a scientific and standardized assessment index system, produce high-quality forest ecological data products, develop localization of assessment model parameters, and explore forest quality–climate change response mechanisms to provide references for in-depth research to realize the transformation of forest ecosystem quality assessments from historical and status quo assessments to future predictions, and to support the construction of a national ecological civilization.

Funder

National Key Research and Development Plan

Fundamental Research Funds for the Central Non-profit Research Institution of CAF

Publisher

MDPI AG

Subject

Forestry

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