1997-2016年黄渤海浮游植物（以表层叶绿素a浓度为表征）物候变化的遥感研究

The spatial and temporal pattern of chlorophyll-a concentration is widely concerned topic in Bohai and Yellow Seas (BYS), with the background of coastal eutrophication and global climate change. At present, many studies in phytoplankton biomass in BYS have examined the changes in magnitude of chlorophyll-a concentration, but little has been done to examine the change in the timing of the growing period of phytoplankton biomass. In recent years, phytoplankton phenology has been successfully proposed as a significant indicator to monitor the variability of marine phytoplankton and detect its response to changes of environmental conditions. Many effective methods and theoretical foundations have been provided from the previous successful studies over global and regional scales. In this project, we proposed to extract the typical metrics of phytoplankton phenology (number of growing period, timing of initiation, timing of peak, timing of termination, and duration of growing period) over the BYS from the remotely sensed chlorophyll-a data (1997-2016), and describe the temporal change and geographic pattern of phytoplankton phenology. The environmental conditions such as water depth, sea surface temperature, sea surface wind and global climatic changes will be examined to address the coupling relationships between phenological changes of marine phytoplankton biomass and the changes of marine environmental conditions. The results of this project are supposed to enhance our understanding of variability in phytoplankton biomass in BYS, and provide theory foundations for interpreting climate changes account for long-term variability of phytoplankton biomass.

在近海富营养化和全球气候变化的大背景下，黄渤海浮游植物生物量的时空变化规律及影响机制是热点。目前，黄渤海浮游植物生物量研究多聚焦于其叶绿素a浓度量值的变化，而对其生长季的变化研究鲜见涉及。近几年，物候期作为反映生物生长季变化的有效指标，被成功引入到海洋浮游植物时空变化规律及其对气候变化的响应研究中，为海洋浮游植物生长季变化研究提供了新的方法和理论依据。本项目拟利用近20年（1997-2016）叶绿素a浓度遥感数据库，分析黄渤海浮游植物各物候特征指标（年内生长季数量、生长季始期、峰值期、生长季终期和生长季持续时间）的多尺度时空变化规律，并结合水深、温度、风场等海洋环境数据及全球性的气候变化事件，探索浮游植物物候变化对海洋环境变化的响应机制。项目的研究结果，能够加深人们对于黄渤海浮游植浮游植物生物量时空变化规律的认识，对揭示浮游植物长期变化及对气候变化的响应机制提供新的理论依据。

长时间序列遥感数据为海洋浮游植物时空变化规律的研究提供了很好的数据基础。本项目以实测和遥感数据为基础，对黄渤海浮游植物生物量及物候变化遥感研究的相关技术和理论开展了系统研究。主要结论如下：（1）实测数据证实了全球标准叶绿素浓度遥感算法在该海区的不适用性；并自主开发了高精度的统计算法（GAM算法），很好的满足了该海区浮游植物生物量和物候变化相关研究的要求。（2）开发了新的多源遥感数据融合重构方法 (M-DINEOF)，解决了长时间序列多源水色遥感数据的高精度融合问题，进一步支撑了浮游植物长期变化遥感的相关研究。（3）利用自主构建的近20年黄渤海浮游植物生物量遥感时间序列数据，对该海区叶绿素生物量和物候变化规律进行了进一步研究，刻画了黄渤海近海和离岸不同的季节变化特征及环境驱动机制。（4）浮游植物生物量在1998-2019年大致呈现了先增后减的趋势，这与营养盐水平的变化基本吻合。

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