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，温带地区水生生态系统的季节演替正在推进，这些变化可能会产生复杂的、可能滞后的反应，导致迄今为止紧密耦合（匹配）过程的脱钩（不匹配）。在 AQUASHIFT 中，我们的目标是确定浮游植物和动物群落过去的相移和滞后反应以及随后的变化。我们的方法侧重于统计数据探索、时间序列分析和建模，基于浮游生物的长期记录（24 年）、来自浅层、多聚体的物理和化学数据。富营养化 Müggelsee（柏林）。我们预计将通过热状况和物种相互作用的变化将直接温度驱动的响应与间接响应分开。 Müggelsee 的条件和春季浮游植物的发育建立在先前的统计分析的基础上，并将由并行时间序列分析产生的随机项进行补充。该模型将与现有的湖泊物理模型相结合。用于预测在一系列气候变化情景下浮游植物春季开花的时间和强度的变化。