---
_id: '11640'
abstract:
- lang: eng
text: Spatially explicit population genetic models have long been developed, yet
have rarely been used to test hypotheses about the spatial distribution of genetic
diversity or the genetic divergence between populations. Here, we use spatially
explicit coalescence simulations to explore the properties of the island and the
two-dimensional stepping stone models under a wide range of scenarios with spatio-temporal
variation in deme size. We avoid the simulation of genetic data, using the fact
that under the studied models, summary statistics of genetic diversity and divergence
can be approximated from coalescence times. We perform the simulations using gridCoal,
a flexible spatial wrapper for the software msprime (Kelleher et al., 2016, Theoretical
Population Biology, 95, 13) developed herein. In gridCoal, deme sizes can change
arbitrarily across space and time, as well as migration rates between individual
demes. We identify different factors that can cause a deviation from theoretical
expectations, such as the simulation time in comparison to the effective deme
size and the spatio-temporal autocorrelation across the grid. Our results highlight
that FST, a measure of the strength of population structure, principally depends
on recent demography, which makes it robust to temporal variation in deme size.
In contrast, the amount of genetic diversity is dependent on the distant past
when Ne is large, therefore longer run times are needed to estimate Ne than FST.
Finally, we illustrate the use of gridCoal on a real-world example, the range
expansion of silver fir (Abies alba Mill.) since the last glacial maximum, using
different degrees of spatio-temporal variation in deme size.
acknowledgement: ES was supported by an IST studentship provided by IST Austria. BT
was funded by the European Union's Horizon 2020 research and innovation programme
under the Marie Sklodowska-Curie Independent Fellowship (704172, RACE). This project
received further funding awarded to KC from the Swiss National Science Foundation
(SNSF CRSK-3_190288) and the Swiss Federal Research Institute WSL. We thank Nick
Barton for many invaluable discussions and his comments on the thesis chapter and
this manuscript. We thank Peter Ralph and Jerome Kelleher for useful discussions
and Bisschop Gertjan for comments on this manuscript. We thank Fortunat Joos for
providing us with the raw data from the LPX-Bern model for silver fir, and Willy
Tinner for helpful insights about the demographic history of silver fir. We also
thank the editor Alana Alexander for useful comments and advice on the manuscript.
Open access funding provided by Eidgenossische Technische Hochschule Zurich.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Eniko
full_name: Szep, Eniko
id: 485BB5A4-F248-11E8-B48F-1D18A9856A87
last_name: Szep
- first_name: Barbora
full_name: Trubenova, Barbora
id: 42302D54-F248-11E8-B48F-1D18A9856A87
last_name: Trubenova
orcid: 0000-0002-6873-2967
- first_name: Katalin
full_name: Csilléry, Katalin
last_name: Csilléry
citation:
ama: Szep E, Trubenova B, Csilléry K. Using gridCoal to assess whether standard
population genetic theory holds in the presence of spatio-temporal heterogeneity
in population size. Molecular Ecology Resources. 2022;22(8):2941-2955.
doi:10.1111/1755-0998.13676
apa: Szep, E., Trubenova, B., & Csilléry, K. (2022). Using gridCoal to assess
whether standard population genetic theory holds in the presence of spatio-temporal
heterogeneity in population size. Molecular Ecology Resources. Wiley. https://doi.org/10.1111/1755-0998.13676
chicago: Szep, Eniko, Barbora Trubenova, and Katalin Csilléry. “Using GridCoal to
Assess Whether Standard Population Genetic Theory Holds in the Presence of Spatio-Temporal
Heterogeneity in Population Size.” Molecular Ecology Resources. Wiley,
2022. https://doi.org/10.1111/1755-0998.13676.
ieee: E. Szep, B. Trubenova, and K. Csilléry, “Using gridCoal to assess whether
standard population genetic theory holds in the presence of spatio-temporal heterogeneity
in population size,” Molecular Ecology Resources, vol. 22, no. 8. Wiley,
pp. 2941–2955, 2022.
ista: Szep E, Trubenova B, Csilléry K. 2022. Using gridCoal to assess whether standard
population genetic theory holds in the presence of spatio-temporal heterogeneity
in population size. Molecular Ecology Resources. 22(8), 2941–2955.
mla: Szep, Eniko, et al. “Using GridCoal to Assess Whether Standard Population Genetic
Theory Holds in the Presence of Spatio-Temporal Heterogeneity in Population Size.”
Molecular Ecology Resources, vol. 22, no. 8, Wiley, 2022, pp. 2941–55,
doi:10.1111/1755-0998.13676.
short: E. Szep, B. Trubenova, K. Csilléry, Molecular Ecology Resources 22 (2022)
2941–2955.
date_created: 2022-07-24T22:01:43Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2023-08-03T12:11:01Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.1111/1755-0998.13676
ec_funded: 1
external_id:
isi:
- '000825873600001'
file:
- access_level: open_access
checksum: 3102e203e77b884bffffdbe8e548da88
content_type: application/pdf
creator: dernst
date_created: 2023-02-02T08:11:23Z
date_updated: 2023-02-02T08:11:23Z
file_id: '12477'
file_name: 2022_MolecularEcologyRes_Szep.pdf
file_size: 6431779
relation: main_file
success: 1
file_date_updated: 2023-02-02T08:11:23Z
has_accepted_license: '1'
intvolume: ' 22'
isi: 1
issue: '8'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '11'
oa: 1
oa_version: Published Version
page: 2941-2955
project:
- _id: 25AEDD42-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '704172'
name: Rate of Adaptation in Changing Environment
publication: Molecular Ecology Resources
publication_identifier:
eissn:
- 1755-0998
issn:
- 1755-098X
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Using gridCoal to assess whether standard population genetic theory holds in
the presence of spatio-temporal heterogeneity in population size
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 22
year: '2022'
...
---
_id: '6637'
abstract:
- lang: eng
text: The environment changes constantly at various time scales and, in order to
survive, species need to keep adapting. Whether these species succeed in avoiding
extinction is a major evolutionary question. Using a multilocus evolutionary model
of a mutation‐limited population adapting under strong selection, we investigate
the effects of the frequency of environmental fluctuations on adaptation. Our
results rely on an “adaptive‐walk” approximation and use mathematical methods
from evolutionary computation theory to investigate the interplay between fluctuation
frequency, the similarity of environments, and the number of loci contributing
to adaptation. First, we assume a linear additive fitness function, but later
generalize our results to include several types of epistasis. We show that frequent
environmental changes prevent populations from reaching a fitness peak, but they
may also prevent the large fitness loss that occurs after a single environmental
change. Thus, the population can survive, although not thrive, in a wide range
of conditions. Furthermore, we show that in a frequently changing environment,
the similarity of threats that a population faces affects the level of adaptation
that it is able to achieve. We check and supplement our analytical results with
simulations.
acknowledgement: The authors would like to thank to Tiago Paixao and Nick Barton for
useful comments and advice.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Barbora
full_name: Trubenova, Barbora
id: 42302D54-F248-11E8-B48F-1D18A9856A87
last_name: Trubenova
orcid: 0000-0002-6873-2967
- first_name: 'Martin '
full_name: 'Krejca, Martin '
last_name: Krejca
- first_name: Per Kristian
full_name: Lehre, Per Kristian
last_name: Lehre
- first_name: Timo
full_name: Kötzing, Timo
last_name: Kötzing
citation:
ama: 'Trubenova B, Krejca M, Lehre PK, Kötzing T. Surfing on the seascape: Adaptation
in a changing environment. Evolution. 2019;73(7):1356-1374. doi:10.1111/evo.13784'
apa: 'Trubenova, B., Krejca, M., Lehre, P. K., & Kötzing, T. (2019). Surfing
on the seascape: Adaptation in a changing environment. Evolution. Wiley.
https://doi.org/10.1111/evo.13784'
chicago: 'Trubenova, Barbora, Martin Krejca, Per Kristian Lehre, and Timo Kötzing.
“Surfing on the Seascape: Adaptation in a Changing Environment.” Evolution.
Wiley, 2019. https://doi.org/10.1111/evo.13784.'
ieee: 'B. Trubenova, M. Krejca, P. K. Lehre, and T. Kötzing, “Surfing on the seascape:
Adaptation in a changing environment,” Evolution, vol. 73, no. 7. Wiley,
pp. 1356–1374, 2019.'
ista: 'Trubenova B, Krejca M, Lehre PK, Kötzing T. 2019. Surfing on the seascape:
Adaptation in a changing environment. Evolution. 73(7), 1356–1374.'
mla: 'Trubenova, Barbora, et al. “Surfing on the Seascape: Adaptation in a Changing
Environment.” Evolution, vol. 73, no. 7, Wiley, 2019, pp. 1356–74, doi:10.1111/evo.13784.'
short: B. Trubenova, M. Krejca, P.K. Lehre, T. Kötzing, Evolution 73 (2019) 1356–1374.
date_created: 2019-07-14T21:59:20Z
date_published: 2019-07-01T00:00:00Z
date_updated: 2023-08-29T06:31:14Z
day: '01'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.1111/evo.13784
ec_funded: 1
external_id:
isi:
- '000474031600001'
file:
- access_level: open_access
checksum: 9831ca65def2d62498c7b08338b6d237
content_type: application/pdf
creator: apreinsp
date_created: 2019-07-16T06:08:31Z
date_updated: 2020-07-14T12:47:34Z
file_id: '6643'
file_name: 2019_Evolution_TrubenovaBarbora.pdf
file_size: 815416
relation: main_file
file_date_updated: 2020-07-14T12:47:34Z
has_accepted_license: '1'
intvolume: ' 73'
isi: 1
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 1356-1374
project:
- _id: 25AEDD42-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '704172'
name: Rate of Adaptation in Changing Environment
- _id: 25B1EC9E-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '618091'
name: Speed of Adaptation in Population Genetics and Evolutionary Computation
publication: Evolution
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Surfing on the seascape: Adaptation in a changing environment'
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 73
year: '2019'
...
---
_id: '6795'
abstract:
- lang: eng
text: The green‐beard effect is one proposed mechanism predicted to underpin the
evolu‐tion of altruistic behavior. It relies on the recognition and the selective
help of altruists to each other in order to promote and sustain altruistic behavior.
However, this mechanism has often been dismissed as unlikely or uncommon, as it
is assumed that both the signaling trait and altruistic trait need to be encoded
by the same gene or through tightly linked genes. Here, we use models of indirect
genetic effects (IGEs) to find the minimum correlation between the signaling and
altruistic trait required for the evolution of the latter. We show that this correlation
threshold depends on the strength of the interaction (influence of the green beard
on the expression of the altruistic trait), as well as the costs and benefits
of the altruistic behavior. We further show that this correlation does not necessarily
have to be high and support our analytical results by simulations.
article_processing_charge: No
article_type: original
author:
- first_name: Barbora
full_name: Trubenova, Barbora
id: 42302D54-F248-11E8-B48F-1D18A9856A87
last_name: Trubenova
orcid: 0000-0002-6873-2967
- first_name: Reinmar
full_name: Hager, Reinmar
last_name: Hager
citation:
ama: Trubenova B, Hager R. Green beards in the light of indirect genetic effects.
Ecology and Evolution. 2019;9(17):9597-9608. doi:10.1002/ece3.5484
apa: Trubenova, B., & Hager, R. (2019). Green beards in the light of indirect
genetic effects. Ecology and Evolution. Wiley. https://doi.org/10.1002/ece3.5484
chicago: Trubenova, Barbora, and Reinmar Hager. “Green Beards in the Light of Indirect
Genetic Effects.” Ecology and Evolution. Wiley, 2019. https://doi.org/10.1002/ece3.5484.
ieee: B. Trubenova and R. Hager, “Green beards in the light of indirect genetic
effects,” Ecology and Evolution, vol. 9, no. 17. Wiley, pp. 9597–9608,
2019.
ista: Trubenova B, Hager R. 2019. Green beards in the light of indirect genetic
effects. Ecology and Evolution. 9(17), 9597–9608.
mla: Trubenova, Barbora, and Reinmar Hager. “Green Beards in the Light of Indirect
Genetic Effects.” Ecology and Evolution, vol. 9, no. 17, Wiley, 2019, pp.
9597–608, doi:10.1002/ece3.5484.
short: B. Trubenova, R. Hager, Ecology and Evolution 9 (2019) 9597–9608.
date_created: 2019-08-11T21:59:24Z
date_published: 2019-09-01T00:00:00Z
date_updated: 2023-08-29T07:03:10Z
day: '01'
ddc:
- '576'
department:
- _id: NiBa
doi: 10.1002/ece3.5484
ec_funded: 1
external_id:
isi:
- '000479973400001'
file:
- access_level: open_access
checksum: adcb70af4901977d95b8747eeee01bd7
content_type: application/pdf
creator: dernst
date_created: 2019-08-12T07:30:30Z
date_updated: 2020-07-14T12:47:40Z
file_id: '6799'
file_name: 2019_EcologyEvolution_Trubenova.pdf
file_size: 2839636
relation: main_file
file_date_updated: 2020-07-14T12:47:40Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '17'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 9597-9608
project:
- _id: 25AEDD42-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '704172'
name: Rate of Adaptation in Changing Environment
publication: Ecology and Evolution
publication_identifier:
eissn:
- '20457758'
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Green beards in the light of indirect genetic effects
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: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 9
year: '2019'
...