Forward and inverse modelling of eco-evolutionary dynamics: in ecological and economic systems
ETH Zurich, 2022
Online
Hochschulschrift
Zugriff:
Ecological and economic systems are complex adaptive systems, composed of multiple entities structured at different organizational levels – from genes to ecological communities and from individual behavioral rules to national economies –, that interact between themselves and their environment, and experience evolutionary processes. The processes operating at the different organizational scales affect each other, generating complex couplings across scales. Yet, despite this astonishing organizational complexity, ecological and economic systems both display invariant patterns. A fundamental challenge in the study of ecological and economic systems is to identify the general organizational principles from which these patterns originate. Recently, studies have shown that evolutionary processes can occur on similar time scales as ecological processes, generating eco-evolutionary feedbacks which may play an important role on the dynamics of ecological systems. In parallel, studies on economic systems suggest that economic change is determined by analogous eco-evolutionary processes. Yet, our understanding of eco-evolutionary processes and feedback mechanisms in empirical systems is limited, because of the oversimplicity of current eco-evolutionary models and a lack of confrontation with empirical data. By developing novel modelling approaches to improve the modelling of empirical systems, this thesis advances our general understanding of the eco-evolutionary processes and feedbacks shaping the dynamics of ecological and economic systems. Specifically, Chapter 2 presents and analyses an eco-evolutionary model on spatial graphs to understand how eco-evolutionary processes, together with complex habitat structures, influence the phenotypic distribution of biological populations. Chapter 3 presents an inverse modelling framework to estimate the most likely parameter values of dynamical models from empirical data, granting the opportunity to discriminate between competing eco-evolutionary hypotheses. Chapter 4 tests ...
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Forward and inverse modelling of eco-evolutionary dynamics: in ecological and economic systems
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Autor/in / Beteiligte Person: | Boussange, Victor ; Pellissier, Loïc ; Sornette, Didier ; Jentzen, Arnulf ; Suweis, Samir |
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Veröffentlichung: | ETH Zurich, 2022 |
Medientyp: | Hochschulschrift |
DOI: | 10.3929/ethz-b-000598848 |
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