Spatio-temporal dynamics before population collapse
Author(s)Dai, Lei, Ph. D. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Physics.
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Theory predicts that the approach of catastrophic thresholds in natural systems may result in an increasingly slow recovery from small perturbations, a phenomenon called critical slowing down. In this thesis, we used replicate laboratory populations of the budding yeast Saccharomyces cerevisiae for direct observation of critical slowing down in spatio-temporal dynamics before population collapse. In the first project, we mapped the bifurcation diagram experimentally and found that the populations became more vulnerable to disturbance closer to the tipping point. Fluctuations of population density increased in size and timescale near the tipping point, in agreement with the theory. In the second project, we used spatially extended yeast populations to evaluate early warning signals based on spatio-temporal fluctuations. We found that indicators based on fluctuations increased before collapse of connected populations; however, the magnitude of increase was smaller than that observed in isolated populations, as local variation is reduced by dispersal. Furthermore, we propose a generic indicator based on deterministic spatial patterns, recovery length. In our experiments, recovery length increased substantially before population collapse, suggesting that the spatial scale of recovery can provide a warning signal before tipping points in spatially extended systems. In the third project, we characterized how different environmental drivers influence the dynamics of yeast populations. We compared the performance of early warning signals across multiple deteriorating environments. We found that the varying performance is determined by how a system responds to changes in a specific driver, which can be captured by a relation between stability and resilience. Furthermore, we demonstrated that the positive correlation between stability and resilience, as the essential assumption of indicators based on critical slowing down, can break down when multiple environmental drivers are changed simultaneously.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2014.Cataloged from PDF version of thesis.Includes bibliographical references.
DepartmentMassachusetts Institute of Technology. Department of Physics.
Massachusetts Institute of Technology