---
_id: '14711'
abstract:
- lang: eng
text: "In nature, different species find their niche in a range of environments,
each with its unique characteristics. While some thrive in uniform (homogeneous)
landscapes where environmental conditions stay relatively consistent across space,
others traverse the complexities of spatially heterogeneous terrains. Comprehending
how species are distributed and how they interact within these landscapes holds
the key to gaining insights into their evolutionary dynamics while also informing
conservation and management strategies.\r\n\r\nFor species inhabiting heterogeneous
landscapes, when the rate of dispersal is low compared to spatial fluctuations
in selection pressure, localized adaptations may emerge. Such adaptation in response
to varying selection strengths plays an important role in the persistence of populations
in our rapidly changing world. Hence, species in nature are continuously in a
struggle to adapt to local environmental conditions, to ensure their continued
survival. Natural populations can often adapt in time scales short enough for
evolutionary changes to influence ecological dynamics and vice versa, thereby
creating a feedback between evolution and demography. The analysis of this feedback
and the relative contributions of gene flow, demography, drift, and natural selection
to genetic variation and differentiation has remained a recurring theme in evolutionary
biology. Nevertheless, the effective role of these forces in maintaining variation
and shaping patterns of diversity is not fully understood. Even in homogeneous
environments devoid of local adaptations, such understanding remains elusive.
Understanding this feedback is crucial, for example in determining the conditions
under which extinction risk can be mitigated in peripheral populations subject
to deleterious mutation accumulation at the edges of species’ ranges\r\nas well
as in highly fragmented populations.\r\n\r\nIn this thesis we explore both uniform
and spatially heterogeneous metapopulations, investigating and providing theoretical
insights into the dynamics of local adaptation in the latter and examining the
dynamics of load and extinction as well as the impact of joint ecological and
evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided
into 5 chapters.\r\n\r\nChapter 1 provides a general introduction into the subject
matter, clarifying concepts and ideas used throughout the thesis. In chapter 2,
we explore how fast a species distributed across a heterogeneous landscape adapts
to changing conditions marked by alterations in carrying capacity, selection pressure,
and migration rate.\r\n\r\nIn chapter 3, we investigate how migration selection
and drift influences adaptation and the maintenance of variation in a metapopulation
with three habitats, an extension of previous models of adaptation in two habitats.
We further develop analytical approximations for the critical threshold required
for polymorphism to persist.\r\n\r\nThe focus of chapter 4 of the thesis is on
understanding the interplay between ecology and evolution as coupled processes.
We investigate how eco-evolutionary feedback between migration, selection, drift,
and demography influences eco-evolutionary outcomes in marginal populations subject
to deleterious mutation accumulation. Using simulations as well as theoretical
approximations of the coupled dynamics of population size and allele frequency,
we analyze how gene flow from a large mainland source influences genetic load
and population size on an island (i.e., in a marginal population) under genetically
realistic assumptions. Analyses of this sort are important because small isolated
populations, are repeatedly affected by complex interactions between ecological
and evolutionary processes, which can lead to their death. Understanding these
interactions can therefore provide an insight into the conditions under which
extinction risk can be mitigated in peripheral populations thus, contributing
to conservation and restoration efforts.\r\n\r\nChapter 5 extends the analysis
in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation)
and extinction risk in a metapopulation. We explore the role of gene flow, selection,
and dominance on load and extinction risk and further pinpoint critical thresholds
required for metapopulation persistence.\r\n\r\nOverall this research contributes
to our understanding of ecological and evolutionary mechanisms that shape species’
persistence in fragmented landscapes, a crucial foundation for successful conservation
efforts and biodiversity management."
acknowledged_ssus:
- _id: SSU
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Oluwafunmilola O
full_name: Olusanya, Oluwafunmilola O
id: 41AD96DC-F248-11E8-B48F-1D18A9856A87
last_name: Olusanya
orcid: 0000-0003-1971-8314
citation:
ama: Olusanya OO. Local adaptation, genetic load and extinction in metapopulations.
2024. doi:10.15479/at:ista:14711
apa: Olusanya, O. O. (2024). Local adaptation, genetic load and extinction in
metapopulations. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:14711
chicago: Olusanya, Oluwafunmilola O. “Local Adaptation, Genetic Load and Extinction
in Metapopulations.” Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:14711.
ieee: O. O. Olusanya, “Local adaptation, genetic load and extinction in metapopulations,”
Institute of Science and Technology Austria, 2024.
ista: Olusanya OO. 2024. Local adaptation, genetic load and extinction in metapopulations.
Institute of Science and Technology Austria.
mla: Olusanya, Oluwafunmilola O. Local Adaptation, Genetic Load and Extinction
in Metapopulations. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:14711.
short: O.O. Olusanya, Local Adaptation, Genetic Load and Extinction in Metapopulations,
Institute of Science and Technology Austria, 2024.
date_created: 2023-12-26T22:49:53Z
date_published: 2024-01-19T00:00:00Z
date_updated: 2024-01-26T12:00:54Z
day: '19'
ddc:
- '576'
degree_awarded: PhD
department:
- _id: NiBa
- _id: GradSch
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ec_funded: 1
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oa: 1
oa_version: Published Version
page: '183'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: c08d3278-5a5b-11eb-8a69-fdb09b55f4b8
grant_number: P32896
name: Causes and consequences of population fragmentation
- _id: 34c872fe-11ca-11ed-8bc3-8534b82131e6
grant_number: '26380'
name: Polygenic Adaptation in a Metapopulation
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
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supervisor:
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Jitka
full_name: Polechova, Jitka
last_name: Polechova
- first_name: Himani
full_name: Sachdeva, Himani
last_name: Sachdeva
title: Local adaptation, genetic load and extinction in metapopulations
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...
---
_id: '14821'
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Heloisa
full_name: Chiossi, Heloisa
id: 2BBA502C-F248-11E8-B48F-1D18A9856A87
last_name: Chiossi
citation:
ama: Chiossi HSC. Adaptive hierarchical representations in the hippocampus. 2024.
doi:10.15479/at:ista:14821
apa: Chiossi, H. S. C. (2024). Adaptive hierarchical representations in the hippocampus.
Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:14821
chicago: Chiossi, Heloisa S. C. “Adaptive Hierarchical Representations in the Hippocampus.”
Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:14821.
ieee: H. S. C. Chiossi, “Adaptive hierarchical representations in the hippocampus,”
Institute of Science and Technology Austria, 2024.
ista: Chiossi HSC. 2024. Adaptive hierarchical representations in the hippocampus.
Institute of Science and Technology Austria.
mla: Chiossi, Heloisa S. C. Adaptive Hierarchical Representations in the Hippocampus.
Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:14821.
short: H.S.C. Chiossi, Adaptive Hierarchical Representations in the Hippocampus,
Institute of Science and Technology Austria, 2024.
date_created: 2024-01-16T14:25:21Z
date_published: 2024-01-19T00:00:00Z
date_updated: 2024-02-01T09:50:29Z
day: '19'
ddc:
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degree_awarded: PhD
department:
- _id: GradSch
- _id: JoCs
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ec_funded: 1
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creator: hchiossi
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file_id: '14838'
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date_created: 2024-01-19T11:03:59Z
date_updated: 2024-01-19T11:03:59Z
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language:
- iso: eng
month: '01'
oa_version: Published Version
page: '89'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
title: Adaptive hierarchical representations in the hippocampus
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2024'
...
---
_id: '15020'
abstract:
- lang: eng
text: "This thesis consists of four distinct pieces of work within theoretical biology,
with two themes in common: the concept of optimization in biological systems,
and the use of information-theoretic tools to quantify biological stochasticity
and statistical uncertainty.\r\nChapter 2 develops a statistical framework for
studying biological systems which we believe to be optimized for a particular
utility function, such as retinal neurons conveying information about visual stimuli.
We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the
expected utility. We explore how such priors aid inference of system parameters
with limited data and enable optimality hypothesis testing: is the utility higher
than by chance?\r\nChapter 3 examines the ultimate biological optimization process:
evolution by natural selection. As some individuals survive and reproduce more
successfully than others, populations evolve towards fitter genotypes and phenotypes.
We formalize this as accumulation of genetic information, and use population genetics
theory to study how much such information can be accumulated per generation and
maintained in the face of random mutation and genetic drift. We identify the population
size and fitness variance as the key quantities that control information accumulation
and maintenance.\r\nChapter 4 reuses the concept of genetic information from Chapter
3, but from a different perspective: we ask how much genetic information organisms
actually need, in particular in the context of gene regulation. For example, how
much information is needed to bind transcription factors at correct locations
within the genome? Population genetics provides us with a refined answer: with
an increasing population size, populations achieve higher fitness by maintaining
more genetic information. Moreover, regulatory parameters experience selection
pressure to optimize the fitness-information trade-off, i.e. minimize the information
needed for a given fitness. This provides an evolutionary derivation of the optimization
priors introduced in Chapter 2.\r\nChapter 5 proves an upper bound on mutual information
between a signal and a communication channel output (such as neural activity).
Mutual information is an important utility measure for biological systems, but
its practical use can be difficult due to the large dimensionality of many biological
channels. Sometimes, a lower bound on mutual information is computed by replacing
the high-dimensional channel outputs with decodes (signal estimates). Our result
provides a corresponding upper bound, provided that the decodes are the maximum
posterior estimates of the signal."
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
citation:
ama: Hledik M. Genetic information and biological optimization. 2024. doi:10.15479/at:ista:15020
apa: Hledik, M. (2024). Genetic information and biological optimization.
Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:15020
chicago: Hledik, Michal. “Genetic Information and Biological Optimization.” Institute
of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:15020.
ieee: M. Hledik, “Genetic information and biological optimization,” Institute of
Science and Technology Austria, 2024.
ista: Hledik M. 2024. Genetic information and biological optimization. Institute
of Science and Technology Austria.
mla: Hledik, Michal. Genetic Information and Biological Optimization. Institute
of Science and Technology Austria, 2024, doi:10.15479/at:ista:15020.
short: M. Hledik, Genetic Information and Biological Optimization, Institute of
Science and Technology Austria, 2024.
date_created: 2024-02-23T14:02:04Z
date_published: 2024-02-23T00:00:00Z
date_updated: 2024-03-06T14:22:52Z
day: '23'
ddc:
- '576'
- '519'
degree_awarded: PhD
department:
- _id: GradSch
- _id: NiBa
- _id: GaTk
doi: 10.15479/at:ista:15020
ec_funded: 1
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keyword:
- Theoretical biology
- Optimality
- Evolution
- Information
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: '158'
project:
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call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 2665AAFE-B435-11E9-9278-68D0E5697425
grant_number: RGP0034/2018
name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
- _id: bd6958e0-d553-11ed-ba76-86eba6a76c00
grant_number: '101055327'
name: Understanding the evolution of continuous genomes
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
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relation: part_of_dissertation
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status: public
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
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
title: Genetic information and biological optimization
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2024'
...
---
_id: '15101'
acknowledged_ssus:
- _id: EM-Fac
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: JingJing
full_name: Chen, JingJing
id: 2C4E65C8-F248-11E8-B48F-1D18A9856A87
last_name: Chen
citation:
ama: Chen J. Developmental transformation of nanodomain coupling between Ca2+ channels
and release sensors at a central GABAergic synapse. 2024. doi:10.15479/at:ista:15101
apa: Chen, J. (2024). Developmental transformation of nanodomain coupling between
Ca2+ channels and release sensors at a central GABAergic synapse. Institute
of Science and Technology Austria. https://doi.org/10.15479/at:ista:15101
chicago: Chen, JingJing. “Developmental Transformation of Nanodomain Coupling between
Ca2+ Channels and Release Sensors at a Central GABAergic Synapse.” Institute of
Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:15101.
ieee: J. Chen, “Developmental transformation of nanodomain coupling between Ca2+
channels and release sensors at a central GABAergic synapse,” Institute of Science
and Technology Austria, 2024.
ista: Chen J. 2024. Developmental transformation of nanodomain coupling between
Ca2+ channels and release sensors at a central GABAergic synapse. Institute of
Science and Technology Austria.
mla: Chen, JingJing. Developmental Transformation of Nanodomain Coupling between
Ca2+ Channels and Release Sensors at a Central GABAergic Synapse. Institute
of Science and Technology Austria, 2024, doi:10.15479/at:ista:15101.
short: J. Chen, Developmental Transformation of Nanodomain Coupling between Ca2+
Channels and Release Sensors at a Central GABAergic Synapse, Institute of Science
and Technology Austria, 2024.
date_created: 2024-03-11T10:09:54Z
date_published: 2024-03-11T00:00:00Z
date_updated: 2024-03-14T13:14:19Z
day: '11'
ddc:
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degree_awarded: PhD
department:
- _id: GradSch
- _id: PeJo
doi: 10.15479/at:ista:15101
ec_funded: 1
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language:
- iso: eng
month: '03'
oa_version: Published Version
page: '84'
project:
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '692692'
name: Biophysics and circuit function of a giant cortical glumatergic synapse
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00312
name: The Wittgenstein Prize
- _id: bd88be38-d553-11ed-ba76-81d5a70a6ef5
grant_number: P36232
name: Mechanisms of GABA release in hippocampal circuits
- _id: 26B66A3E-B435-11E9-9278-68D0E5697425
grant_number: '25383'
name: Development of nanodomain coupling between Ca2+ channels and release sensors
at a central inhibitory synapse
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '14843'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Peter M
full_name: Jonas, Peter M
id: 353C1B58-F248-11E8-B48F-1D18A9856A87
last_name: Jonas
orcid: 0000-0001-5001-4804
title: Developmental transformation of nanodomain coupling between Ca2+ channels and
release sensors at a central GABAergic synapse
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2024'
...
---
_id: '15094'
abstract:
- lang: eng
text: "Point sets, geometric networks, and arrangements of hyperplanes are fundamental
objects in\r\ndiscrete geometry that have captivated mathematicians for centuries,
if not millennia. This\r\nthesis seeks to cast new light on these structures by
illustrating specific instances where a\r\ntopological perspective, specifically
through discrete Morse theory and persistent homology,\r\nprovides valuable insights.\r\n\r\nAt
first glance, the topology of these geometric objects might seem uneventful: point
sets\r\nessentially lack of topology, arrangements of hyperplanes are a decomposition
of Rd, which\r\nis a contractible space, and the topology of a network primarily
involves the enumeration\r\nof connected components and cycles within the network.
However, beneath this apparent\r\nsimplicity, there lies an array of intriguing
structures, a small subset of which will be uncovered\r\nin this thesis.\r\n\r\nFocused
on three case studies, each addressing one of the mentioned objects, this work\r\nwill
showcase connections that intertwine topology with diverse fields such as combinatorial\r\ngeometry,
algorithms and data structures, and emerging applications like spatial biology.\r\n\r\n"
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Sebastiano
full_name: Cultrera di Montesano, Sebastiano
id: 34D2A09C-F248-11E8-B48F-1D18A9856A87
last_name: Cultrera di Montesano
orcid: 0000-0001-6249-0832
citation:
ama: Cultrera di Montesano S. Persistence and Morse theory for discrete geometric
structures. 2024. doi:10.15479/at:ista:15094
apa: Cultrera di Montesano, S. (2024). Persistence and Morse theory for discrete
geometric structures. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:15094
chicago: Cultrera di Montesano, Sebastiano. “Persistence and Morse Theory for Discrete
Geometric Structures.” Institute of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:15094.
ieee: S. Cultrera di Montesano, “Persistence and Morse theory for discrete geometric
structures,” Institute of Science and Technology Austria, 2024.
ista: Cultrera di Montesano S. 2024. Persistence and Morse theory for discrete geometric
structures. Institute of Science and Technology Austria.
mla: Cultrera di Montesano, Sebastiano. Persistence and Morse Theory for Discrete
Geometric Structures. Institute of Science and Technology Austria, 2024, doi:10.15479/at:ista:15094.
short: S. Cultrera di Montesano, Persistence and Morse Theory for Discrete Geometric
Structures, Institute of Science and Technology Austria, 2024.
date_created: 2024-03-08T15:28:10Z
date_published: 2024-03-08T00:00:00Z
date_updated: 2024-03-20T09:36:57Z
day: '08'
ddc:
- '514'
- '500'
- '516'
degree_awarded: PhD
department:
- _id: GradSch
- _id: HeEd
doi: 10.15479/at:ista:15094
ec_funded: 1
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last_name: Edelsbrunner
orcid: 0000-0002-9823-6833
title: Persistence and Morse theory for discrete geometric structures
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