Advances in influencing mechanism and model of total climatic production factors of plant phenology change

Abstract

<p indent="0mm">Phenology is an important indicator of climate change. It is not only the key to vegetation dynamic simulation, but also directly affects the simulation accuracy of terrestrial carbon cycle and atmospheric general circulation model. This paper summarizes the research status of plant phenology from two aspects: phenological change mechanism and phenological simulation model, and analyzes the research trend of phenology. It points out that most of the current phenological studies only consider the impact of a single climate factor or a few climate factors, and there are still few studies involved in the interaction of multiple climate factors, let alone the interaction of total climate production factors determining plant phenology. Due to the limitation of the understanding of phenological change mechanism and the study of species, the existing phenological models cannot reflect the authenticity of vegetation growth, nor can they effectively simulate the phenological period. The paper points out that it is essential to study the relationship between phenology and total climatic production factors in order to comprehensively understand the mechanism of phenological change. Based on the fact that plant photosynthesis is the most important phenological influencing factor, this paper puts forward the viewpoint of using climate production potential as the driving factor of plant phenological change. Climate production potential not only reflects the comprehensive effect of climate and environmental factors on plant production and their consistency of these factors in the whole process of plant growth, but also includes the interaction between biological factors and environmental factors and the impact of extreme weather and climate events, which is able to realize the accurate simulation of phenology. The future phenological research directions proposed in this paper will help enrich phenological knowledge and improve the simulation accuracy of land carbon cycle model and atmospheric circulation model.