中国北方自然植物春季物候模拟研究

Seasonal dynamic of vegetation is an important background of climate change. Phenology models can bridge the gap between the extensive spatial scales available from satellite-derived observations and the linkage to driving variables that can potentially be derived from ground observations. This has important scientific implications for revealing the consistency of plant phenology responses to climate change and assessing the accuracy of remote sensing phenology. Using phenological data of several local trees and grass, daily meteorological data, and remote sensing data, spatial and temperal modeling of spring phenology were carried out across northern China. First，we intend to find the key meteorological factors, which lead to the variation of ground spring phenology, by developing and assessing several multi-meteorological factors drived spring phenology models for each species at each station. Then, we will examine external performances of each optimum local species-specific model and select the local species-specific models with maximum effective predictions as the regional unified models. Based on the regional unified models, the spatio-temperal patterns of spring phenology of local species across northern China will be reconstructed. Furthermore, we will apply the phenological models that developed at station-species level to satellite-derived start of growing season and assess the performance of models, in an attempt to find the the key meteorological factors, which lead to the variation of remote sencing spring phenology. Finally, we will estiblish the bioclimatic index model to reconstruct the spatio-temperal patterns of bioclimatic spring phenology across northern China. The compartions and evaluations of the spatio-temperal spring phenology patterns will be carried out between the ground observations and satellite observations.

植被的季节动态是气候变化研究的重要背景，通过构建春季物候模型实现从地点到区域、单种到群落的尺度转化，对于揭示植物物候对气候变化响应的区域一致性和验证遥感物候监测的准确性具有重要科学意义。本研究拟在收集中国北方自然植物物候数据、气象数据和遥感数据的基础上，首先，在站点尺度上构建和优选多因子驱动的春季物候模型，寻找影响地面春季物候变化的主要气象因子，并通过时空外推检验建立区域统一物候模型，重建中国北方植物春季物候的时空格局；其次，在植被类型分区下，提取遥感生长季节开始日期的时空格局，将春季物候模型应用于遥感生长季节开始日期的模拟，寻找影响遥感春季物候变化的主要气象因子；最后，基于地面春季物候模型和遥感春季物候模型筛选出的气象因子，构建生物气象指标模型，反演中国北方气候生长季节开始日期的时空格局，并与地面单种模拟、遥感监测的生长季节开始日期在同一空间尺度上进行比较和评估。

本项目根据中国气象局农业气象站观测的自然植物物候数据，构建了近三十年来中国自然植物物候数据库，使用室内实验、数学模拟和遥感监测相结合的方法，围绕气候生长季节时空变化特征、自然植物春季物候期模拟和遥感植被春季物候监测及地面验证三个方面，基于偏差法计算了中国北方地区连续地理空间上稳定通过不同界限温度（≥0℃、5℃、10℃、15℃和20℃）的起止日期、持续日数和积温，综合分析了气候变化背景下气候生长季节初、终日及热量资源的时空格局的变化特征。使用加入去趋势分析的最佳期间气温-物候模型在中国北方地区40个站点上开展了旱柳花期对气候变化响应的敏感性研究。使用人工气候箱对典型牧草返青期进行了气候控制性实验，测定了内蒙古草原优势牧草（羊草和针茅）返青的起点温度，获取了第一手的羊草和针茅返青期的关键生理参数。构建和检验了草本植物物候机理模型，模拟了内蒙古地区14种牧草的物候变化情况，并评估了未来气候变化情景下不同物种物候期的时空响应特征。在遥感物候季节划分方法地面验证的基础上，对近三十年内蒙古地区不同植被类型遥感物候的时空变化特征及其与气象因子的相互作用关系进行了分析。本项目的研究成果为深化我国陆地生态系统对气候变化的物候响应研究具有一定的理论意义和参考价值。