Resilience is the ability of a dynamical system (such as an ecosystem) to quickly recover from short-term perturbations and return to its previous state. High resilience implies an ability for a system to withstand shocks, whereas declining resilience would leave a system vulnerable to shocks or to passing ‘tipping points’ beyond which a regime shift to an alternative stable state (if it exists) becomes inevitable. It has been hypothesised that these tipping points may under certain circumstances be preceded by ‘early warning signals’ (EWS) that are detectable through statistical analysis, which could in theory provide invaluable alerts to humanity prior to future environmental regime shifts. However, reliably detecting EWS has proven tricky in practice, and producing robust measures of changing resilience and EWS remains a major research challenge. Measuring and understanding changes in resilience in ecosystems and the carbon cycle has become a major theme in my research, and has played a central role in several projects:
Post-Doc 1.2: Can early warning signals be reliably detected in the Cenozoic palaeoclimate record? (2016)
In the summer of 2016 I received funding from the EPSRC/ReCoVER network for a 3 month Post-Doctoral Research Fellow position at the University of Southampton, which follows on from my tipping point / early warning research in my PhD. You can find more information on the Climate-Biosphere Feedbacks & Tipping Points page.
Post-Doc 1.4: Agent-based models for the analysis of early warning signals of ecosystem tipping points (Uni. Southampton, 2017)
In this pilot study project (also funded by the ReCoVER Network), we aimed to extend our understanding of ecosystem functioning in lakes undergoing eutrophication, and how it is affected by changes in biodiversity prior to the critical transition to a eutrophic state. As part of this I have developed an algorithm for reconstructing ecosystem community structure from diatom palaeoabundance data and inferring network stability as well as the novel metric of “ecological memory”. The final paper is in progress.
Post-Doc 2.2: Quantifying the changing resilience of the climate system and ecosystems (Uni. Exeter / Stockholm Resilience Centre, 2018-2020)
During my postdoc at SRC I also worked part-time on a Leverhulme-funded Research Project Grant led by PI Prof. Tim Lenton at the University of Exeter on ecosystem resilience monitoring. For this project I’m focusing on using big data from remote sensing and vegetation models to perform high resolution ecosystem resilience monitoring (with Amazon and Boreal forest ecoregions the primary target), with the aim of understanding how increasing climate variability and declining biodiversity is affecting ecological resilience
Dr. David Armstrong MᶜKay 