---
OA_place: publisher
_id: '8574'
abstract:
- lang: eng
  text: "This thesis concerns itself with the interactions of evolutionary and ecological
    forces and the consequences on genetic diversity and the ultimate survival of
    populations. It is important to understand what signals processes \r\nleave on
    the genome and what we can infer from such data, which is usually abundant but
    noisy. Furthermore, understanding how and when populations adapt or go extinct
    is important for practical purposes,  such as the genetic management of populations,
    as well as for theoretical questions, since local adaptation can be the first
    step toward speciation. \r\nIn Chapter 2, we introduce the method of maximum entropy
    to approximate the demographic changes of a population in a simple setting, namely
    the logistic growth model with immigration. We show that this method is not only
    a powerful \r\ntool in physics but can be gainfully applied in an ecological framework.
    We investigate how well it approximates the real \r\nbehavior of the system, and
    find that is does so, even in unexpected situations. Finally, we illustrate how
    it can model changing environments.\r\nIn Chapter 3, we analyze the co-evolution
    of allele frequencies and population sizes in an infinite island model.\r\nWe
    give conditions under which polygenic adaptation to a rare habitat is possible.
    The model we use is based on the diffusion approximation, considers eco-evolutionary
    feedback mechanisms (hard selection), and treats both \r\ndrift and environmental
    fluctuations explicitly. We also look at limiting scenarios, for which we derive
    analytical expressions. \r\nIn Chapter 4, we present a coalescent based simulation
    tool to obtain patterns of diversity in a spatially explicit subdivided population,
    in which the demographic history of each subpopulation can be specified. We compare
    \r\nthe results to existing predictions, and explore the relative importance of
    time and space under a variety of spatial arrangements and demographic histories,
    such as expansion and extinction. \r\nIn the last chapter, we give a brief outlook
    to further research. "
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Eniko
  full_name: Szep, Eniko
  id: 485BB5A4-F248-11E8-B48F-1D18A9856A87
  last_name: Szep
citation:
  ama: Szep E. Local adaptation in metapopulations. 2020. doi:<a href="https://doi.org/10.15479/AT:ISTA:8574">10.15479/AT:ISTA:8574</a>
  apa: Szep, E. (2020). <i>Local adaptation in metapopulations</i>. Institute of Science
    and Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:8574">https://doi.org/10.15479/AT:ISTA:8574</a>
  chicago: Szep, Eniko. “Local Adaptation in Metapopulations.” Institute of Science
    and Technology Austria, 2020. <a href="https://doi.org/10.15479/AT:ISTA:8574">https://doi.org/10.15479/AT:ISTA:8574</a>.
  ieee: E. Szep, “Local adaptation in metapopulations,” Institute of Science and Technology
    Austria, 2020.
  ista: Szep E. 2020. Local adaptation in metapopulations. Institute of Science and
    Technology Austria.
  mla: Szep, Eniko. <i>Local Adaptation in Metapopulations</i>. Institute of Science
    and Technology Austria, 2020, doi:<a href="https://doi.org/10.15479/AT:ISTA:8574">10.15479/AT:ISTA:8574</a>.
  short: E. Szep, Local Adaptation in Metapopulations, Institute of Science and Technology
    Austria, 2020.
corr_author: '1'
date_created: 2020-09-28T07:33:38Z
date_published: 2020-09-20T00:00:00Z
date_updated: 2026-04-08T07:21:44Z
day: '20'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: NiBa
doi: 10.15479/AT:ISTA:8574
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has_accepted_license: '1'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: '158'
publication_identifier:
  eissn:
  - 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
title: Local adaptation in metapopulations
type: dissertation
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2020'
...