Climate induced changes in phenology of lake plankton communities: Implications for the match / mismatch of species interactions

气候引起的湖泊浮游生物群落物候变化：对物种相互作用匹配/不匹配的影响

• 批准号: 5429622
• 负责人: Professorin Dr. Rita Adrian, Ph.D.
• 金额: --
• 依托单位: Leibniz-Institut für Gewässerökologie und Binnenfischerei (IGB)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2004
• 资助国家: 德国
• 起止时间: 2003-12-31 至 2009-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5429622?language=en
• 关键词: Climate; induced; changes; phenology; lake

Long term studies suggest that seasonal succession in aquatic ecosystems is currently advancing in temperate latitudes. Those changes are likely to generate complex, and possibly time lagged responses leading to a decoupling (mismatch) of so far tightly coupled (matched) processes. Previous studies have basically focussed on individual species' responses to warming, while neglecting inter-specific interactions. Within AQUASHIFT we aim to identify past phase shifts and time-lagged responses in phyto- and zooplankton communities, and subsequent changes in species interaction induced by observed and projected climate warming. Our methodological approach is focussed on statistical data exploration, time series analysis, and modelling, based upon long-term records (24 years) of plankton, physical and chemical data from shallow, polymictic, eutrophic Müggelsee (Berlin). We anticipate to separate direct temperature driven responses from indirect responses through changes in thermal regime and species interaction. A stochastic and/or deterministic model will be created to describe the linkage between winter and spring meteorological conditions and vernal phytoplankton development in Müggelsee. Model development builds on previous statistical analysis and will be complemented by stochastic terms resulting from the parallel time series analysis. The model will be coupled to an existing lake physics model. This offline-coupled model system will be used to project changes in the timing and intensity of the phytoplankton spring blooms under a range of climate change scenarios.

长期研究表明，水生生态系统的季节成功目前正在温度纬度上进步。这些变化可能会产生复杂的，并且可能的时间滞后响应导致到目前为止紧密耦合（匹配）过程的脱钩（不匹配）。先前的研究基本上集中在单个规格对变暖的反应上，同时忽略了特异性之间的相互作用。在Aquashift中，我们旨在确定植物和浮游动物群落中过去的相移和时置的反应，以及随后被观察和预测的气候变暖引起的物种相互作用变化。我们的方法论方法基于浮游生物的长期记录（24年），来自浅层，多核，富营养的müggelsee（柏林）的长期记录（24年），重点关注统计数据探索，时间序列分析和建模。我们预计，通过热度和物种相互作用的变化，将直接驱动响应与间接响应分开。将创建一个随机模型和/或确定性模型，以描述Müggelsee中冬季和春季气象条件之间的联系以及春季浮游植物的发展。模型开发以先前的统计分析为基础，并将通过平行时间序列分析产生的随机术语完成。该模型将与现有的湖泊物理模型耦合。该离线耦合模型系统将用于在一系列气候变化方案下浮游植物春季血的时间和强度变化。