Indicators of regime shifts in freshwater ecosystems

Regime shifts, characterised by sudden, often irreversible, changes in the composition of biological communities, can have catastrophic impacts on the ecosystem services which society relies on. Classic examples of this phenomenon originate from freshwater ecosystems, where shifts in the structure of a community can lead to cyanobacteria-dominated ecosystems, with potential negative impacts on human and livestock health. Being able to predict impending regime shifts in time to avert them is consequently a critical goal with significant implications for the management of scarce freshwater resources. This project will use long-term monitoring data in combination with advanced modelling techniques to characterise how community composition can change prior to and during a regime shift, and test and develop generalisable methods to predict and prevent such shifts in the future. A key goal in predictive ecology is forecasting the potential for rapid changes in ecosystems, leading to the development of "early warning signals". These are generalisable methods which aim to predict changes in the composition of a community by detecting signals in time series data which are symptomatic of an approaching regime shift. The potential efficacy of such signals has been widely shown in simulation studies, but remains largely untested on real-world data, in part due to the lack of long-term monitoring before and after observed regime shifts. This has raised questions about their suitability to inform management strategies for natural capital. This project will tackle this knowledge gap using a two-pronged approach: analysis of long-term monitoring data from a well-studied lake ecosystem which has undergone a regime shift, and complementary theoretical modelling of the lake community. The Sea of Galilee is the only natural freshwater lake in Israel, and consequently a key resource. Its importance has meant extensive monitoring has been carried out for nearly 50 years, providing exceptional data on the abundances, biomasses, and densities of fish, zooplankton, and phytoplankton species from 1969 until 2018, as well as changes in the lake's chemical composition. The lake's community underwent a major shift in 1994-1995, resulting in a severe deterioration in water quality and an increase in harmful algal blooms. Consequently, data on multiple species and trophic levels are available prior to, during, and after a known regime shift, making it ideal for testing and developing warning signal methods. These exceptional data will be used to parameterise a size-spectra model of the lake community, allowing multiple simulated outcomes of perturbations on the system to be assessed. This project will: (1) assess whether the regime shift in the Sea of Galilee could have been predicted prior to its occurrence, (2) determine how far in advance such warning signals are detectable, (3) examine whether it is better to focus on specific species, trophic levels, or look at the community dynamics as a whole when trying to predict a system's future dynamics, and (4) identify what data should be collected in the future to predict regime shifts. In addition to the specialist training provided by the supervisors, the student will undertake a full range of general courses to enhance their employability and personal development, including training on Statistics, Computing, Research Ethics, Intellectual Property and Enterprise, Bioinformatics, Sampling Methodology, and Research Skills.