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- W202270483 abstract "Ecological systems such as forest and lakes can exhibit multiple stable states, abrupt transitions and self-organization as a control parameter is varied. Understanding the dynamics of these systems and devising easily quantifiable measures with predictive capabilities using the theoretical tools of stochastic dynamics and nonequilibrium statistical physics form the focus of this thesis. First, we study simple ecological models with no spatial degrees of freedom, that show a catastrophic transition as a control parameter is varied and propose a novel early warning signal that exploits two ubiquitous features of ecological systems: nonlinearity and large external fluctuations. It is shown that changes in asymmetry in the distribution of time series data, quantified by changing skewness, is an early warning signal of impending regime shifts. Using simple analytical calculations, model simulations that mimic field measurements and an analysis of real data from abrupt climate change in the Sahara, we study the feasibility of skewness calculations using data available from routine monitoring. Next, we consider a spatially explicit model of collapse of vegetation in one and two spatial dimensions. An analytical calculation based on the mean-field approximation shows that spatial variance and spatial skewness (with an appropriate sign) increase as one approaches the threshold of vegetation collapse. Our numerical calculations show that an increasing spatial variance in conjunction with a reversal in the initial changing trend of spatial skewness is a superior indicator of an impending spatial ecological regime shift when" @default.
- W202270483 created "2016-06-24" @default.
- W202270483 creator A5061597162 @default.
- W202270483 date "2008-01-01" @default.
- W202270483 modified "2023-09-27" @default.
- W202270483 title "Applications of nonequilibrium statistical physics to ecological systems" @default.
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