@article{11640,
  abstract     = {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.},
  author       = {Szep, Eniko and Trubenova, Barbora and Csilléry, Katalin},
  issn         = {1755-0998},
  journal      = {Molecular Ecology Resources},
  number       = {8},
  pages        = {2941--2955},
  publisher    = {Wiley},
  title        = {{Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size}},
  doi          = {10.1111/1755-0998.13676},
  volume       = {22},
  year         = {2022},
}

@article{6637,
  abstract     = {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.},
  author       = {Trubenova, Barbora and Krejca, Martin  and Lehre, Per Kristian and Kötzing, Timo},
  journal      = {Evolution},
  number       = {7},
  pages        = {1356--1374},
  publisher    = {Wiley},
  title        = {{Surfing on the seascape: Adaptation in a changing environment}},
  doi          = {10.1111/evo.13784},
  volume       = {73},
  year         = {2019},
}

@article{6795,
  abstract     = {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.},
  author       = {Trubenova, Barbora and Hager, Reinmar},
  issn         = {20457758},
  journal      = {Ecology and Evolution},
  number       = {17},
  pages        = {9597--9608},
  publisher    = {Wiley},
  title        = {{Green beards in the light of indirect genetic effects}},
  doi          = {10.1002/ece3.5484},
  volume       = {9},
  year         = {2019},
}