Regime shifts in lake ecosystems: Testing theory with long-term observational data and large scale experiments (LakeShift)

• Applicant: Professor Dr. Georgiy Kirillin
• Subject Area: Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
• Term: from 2013 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 241278852

Long-term ecological research has become a cornerstone of the scientific endeavor to better understand ecosystem dynamics and abrupt responses (regime shifts) to variability in environmental changes such as global warming. Theory predicts that regime shifts can be attributed to stochastic events such as extreme events or species invasion, surpassing of critical thresholds or purely by internally generated fluctuations. There is an apparent gap, however, between theoretical frameworks concerning driving forces of food web interactions and regime shifts and their applicability to scenarios actually observed in nature; i.e. testing ecological theory with observational data. The lack of testing ecological theory with observational data in the past has been partly due to the lack of adequate data with respect to the length of the time series and their temporal resolution; given that current scenarios of regime shift theory demand large amounts of data. We will link long-term observational data of lake ecosystems, physical modeling approaches and artificially induced regime shifts in large scale experimental set-ups to tackle the question as to how the frequency and magnitude of environmental fluctuations affect the probability that entire ecosystems or single abiotic and biotic ecosystem levels will shift from one state into another. Moreover, we intend to pinpoint early warning signals via statistical anomalies in ecological time series which precede such abrupt shifts. The value of such studies is manifold. It will lead to a better understanding of the nature of the underlying forces driving observed regime shifts, i.e. whether the relationship between driver and response variables is of a gradual or of a threshold driven nature. It will foster the development of hypothesis to identify important mechanisms driving observed regime shifts. Moreover, it will enhance our capability to predict likely shifts in thermal regime and subsequent changes in the biota observed under future climate change scenarios. Our foremost interest lies in testing whether observed and experimentally initiated regime shifts of various natures, which operate on various time scales (weeks to decades), follow general inherent pattern as formulated by regime shift theory and whether they can be foreseen by early warning signals.

• DFG Programme: Research Grants