Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA23040303)
Vegetation dynamics are driven by both climate change and anthropogenic activities. Under the background of climate change, comprehensive and quantitative analysis of the role and contribution of human activity in vegetation dynamic changes is of great significance for increasing the carbon stocks of vegetation ecosystems and for mitigating climate change. With the construction of ecological civilization and the strengthening of environmental protection awareness, the profound effects of ecological projects on vegetation variation have been gradually recognized. In terms of vegetation ecosystems, ecological projects, as a type of profound anthropogenic activity, have increasingly and deeply impacted the local and regional vegetation. Systematic analysis of the ecological effects of ecological projects on vegetation under the background of climate change is of great theoretical significance to the formulation and implementation of ecological restoration measures. Many studies have quantitatively explored the impact of ecological projects on vegetation dynamics. However, it is difficult to compare their results with different methods. A comprehensive comparison of these quantitative methods would promote the study of vegetation driving mechanisms and the development of restoration ecology and human ecology. This review summaries several quantitative methods of ecological projects’ impact on the vegetation, including regression analysis, residual trend analysis, the biophysical process model-based method, and the threshold segmentation method. We found that the biophysical process model-based method had the highest potential for application, whereas the residual trend analysis and the threshold segmentation method still needed further improvement. At present, the quantitative analysis of ecological projects’ effects on vegetation change mainly focuses on model simulation, while field empirical study and model verification are relatively lacking, which is one of the emphases and difficulties in future research.