四川植物观赏旅游时令时空格局对气候变化的响应与人类适应研究

Monitoring when plant based tourist seasons occur using field obsverved data and satellite data has been an area of growing research interest in recent decades. Based on systematically collecting observed phenophase over Sichuan province from 1980 to 2016, we are going to analyze the trend of changes in phenophase of plants, and to identify the temporal-spatial patterns of changes in timings of plant based tourism season. We will retrieve timings of fall foliage coloration and timings of fall foliage vacation season in Sichuan province, China from a consistently processed MODIS dataset using double logistic function-fitting algorithm. We will use timings of tourism season and corresponding meteorological data from stations of Sichuan to reveal statistical relationships between the changes in timings and mean air temperature/precipitation, and to find out principal factors influencing timings of plant based tourism season both at species and regional scales. Meanwhile, we will analyze the correlations between change in timings of tourism and temperature change for several terms, established the response mode of tourism season changes to climatic change of Sichuan province, and recognized response asymptote temperature of tourism timings to climatic change. Furthermore, we are going to explore the key factors affecting the perceptions of plant-viewing tourism stakeholders to climate change and their functional routes through structural equation model (SEM). The main aim of this project is to understand the linkage of plants phenophases with the tourism industry, to identify the temporal and spatial patterns of the timings of plant based tourism, and to look for the sensitive regions of climate change, and map the timing of important species’ phenophase in critical scenic areas and cities. To enhance the effectiveness of the proposal to climate change adaptation, we will put forward practical strategies, such as establishing scientific incentive mechanisms, to improve the cognition level of the stakeholders with climate change. We hope that the results of the project will contribute the scientific basis for tourism industry to adapt future climate change.

本项目拟以植物花期、叶变色期等物候观测资料为主，进行均一性、同步性分析及标准化等处理，提取物种尺度的植物观赏旅游时令。利用遥感数据（MODIS NDVI），采用Logistic函数拟合法，以叶变色观测数据进行验证，确定区域尺度的秋季叶变色观赏时令。辅以同时段气象数据，采用时间序列分析、空间特征分析、序列相关分析及空间相关分析等方法，揭示物种尺度和区域尺度的四川省植物观赏旅游时令时空变化规律及其与气候变化的关系。确定植物观赏旅游时令对气候变化的响应模式与阈值。识别对气候变化响应敏感的植物观赏活动类型、区域。选择敏感区开展利益相关者气候变化感知调研，基于结构方程模型，分析影响植物观赏旅游利益相关者气候变化感知的关键因素及其作用路径。编制重点景区、城市，主要植物的花期、叶期时序图谱，提出通过提高利益相关者气候变化认知水平，建立科学的激励机制等方式，增强植物观赏旅游业适应气候变化能力的措施。

本项目集成了长时间序列的基于观测站点的枫叶、桃花、果实采摘数据集。对数据进行均一性、同步性分析及标准化等处理，提取了物种尺度的植物观赏旅游时令。利用多源大数据，发展和优化了基于logistic曲线从微博大数据中提取赏樱旅游活动开展时间的方法，提取和重建了中国2010年至2019年赏樱、桃花观赏等旅游活动时间数据集，该数据集通过了物候站点观测数据和与温度条件的验证。研究了物种和区域尺度植物观赏旅游时令的时空变化特征及其与气候变化的关系。确定了植物观赏旅游时令对气候变化的响应模式与响应阈值，识别了对气候变化响应敏感的植物观赏活动类型、区域，并评估其敏感性。明确影响利益相关者气候变化影响感知的关键因素，提出了植物观赏旅游活动适应气候变化的方案。