Match / mismatch of zooplankton- phytoplankton interactions, based on existing long-term information in the North Sea

浮游植物的演替和浮游动物的共存仍然知之甚少，特别是在海洋环境中。关于气候变化如何影响这些有机体及其相互作用，我们仍然非常不确定。然而，对于北海，我们有办法通过分析现有的两个数据库来改变这种情况，一个是高时间分辨率的数据库，另一个是高空间分辨率的数据库，分别是赫尔戈兰路数据库和连续浮游生物记录器数据库。我们将使用多种方法(从标准的线性统计到基于符号动力学方法的高级多变量数据分析)来区分北海的演替模式。我们将确定主要的导向过程，如放牧、光照、营养物质、这些模式中的水文和关键事件，如淡水和咸水入侵，或风暴，它们驱动或触发生物体的时间选择。为了在数据中搜索和识别这样的驱动或触发机制，我们将使用最近引入的Bloom触发平均方法。研究气候异常和全球变暖等关键事件的变化。以这一背景为基础，将确定与过去40年气候变化有关的浮游生物和浮游动物/浮游植物相互作用的共存情况，并调查与气候变化有关的生物匹配-不匹配问题。

Phytoplankton succession and the concurrence of Zooplankton are still poorly understood particularly in marine environments. We are still very unsure as to how climate change affects these organisms and their interactions. For the North Sea, however, we have the means to change this by analysing two existing databases, one with high temporal resolution and one with high spatial resolution, the Helgoland Roads (HR) and Continuous Plankton Recorder (CPR) databases, respectively. We will use a diverse array of methods (from standard linear statistics through to advanced multivariate data analysis based on the method of symbolic dynamics) to differentiate patterns of succession in the North Sea. We will determine the main steering processes e.g. grazing, light, nutrients, hydrography in these patterns and key events such as fresh and saltwater intrusions, or storms, which either drive or trigger timing of organisms. To search and identify such driving or trigger mechanisms within data we will employ the recently introduced method of bloom triggered averaging. We will investigate changes in the key events related to climate anomalies and global warming. Using this backdrop as a basis the co-occurrence of pelagic organisms and zooplankton/phytoplankton interactions will be determined and organism match-mismatch investigated related to climate shifts over the last 40 years.