Probabilistic Measures for Biological Adaptation and Resilience
ORAL
Abstract
The importance of understanding and predicting biological resilience is growing as we become increasingly aware of the consequences of changing climatic conditions. Various approaches to operationalize resilience have been proposed. We adapted a statistical mechanical framework for the time dependent dynamics of biological systems that offers a powerful conceptualization of systems whose response share similarities with heterogeneous forced/dissipative physical systems. In this framework we are concerned with the dynamics of a probabilistic description of observables. We propose and derive a quantitative measure of adaptive resilience. Unlike more common resilience measures, ours takes into account the variability of the time history of the dynamics and the heterogeneity of the organism. Once a measure of success is proposed it quantifies the degree to which a biological system succeeds to adapt to new conditions after being stressed.
* The Authors acknowledge the US Department of Energy for funding.
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Publication: Physical Review E, submitted, 2023.
Presenters
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Juan M M Restrepo
Oak Ridge National Laboratory
Authors
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Juan M M Restrepo
Oak Ridge National Laboratory
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Jorge M Ramirez
Oak Ridge National Laboratory
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Valerio Lucarini
University of Reading
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David Weston
Oak Ridge National Laboratory