Parametric and nonparametric approaches to explain and predict nonlinear population dynamics in changing environments

Many aspects of human societies, from the sustenance of national economies to the control of population health, depend on the dynamics of biological populations within a given environment. Therefore, understanding and predicting the effects of changing environments on the dynamics of biological populations evolving in a continuously changing world is, nowadays, one of the most important challenges in biology. In this thesis we have addressed this challenge using two different approaches. The first approach, called the structural approach, is deductive, i.e., the effects of changing environments on population dynamics are studied using parametric models under equilibrium assumptions. In this context, firstly we have shown that, while the approach was originally introduced to investigate the structural stability of the classic Lotka-Volterra dynamics; it can be applied to a much larger class of nonlinear models and to stochastic systems.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Cenci, Simone.

Advisor dc:contributor.advisor

• Serguei Saavedra.

• Civil and Environmental Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/123224

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/123224