scholarly journals Polygenic local adaptation in metapopulations: A stochastic eco‐evolutionary model

Evolution ◽  
2021 ◽  
Author(s):  
Enikő Szép ◽  
Himani Sachdeva ◽  
Nicholas H. Barton
2020 ◽  
Author(s):  
Enikő Szép ◽  
Himani Sachdeva ◽  
Nick Barton

AbstractThis paper analyses the conditions for local adaptation in a metapopulation with infinitely many islands under a model of hard selection, where population size depends on local fitness. Each island belongs to one of two distinct ecological niches or habitats. Fitness is influenced by an additive trait which is under habitat-dependent directional selection. Our analysis is based on the diffusion approximation and accounts for both genetic drift and demographic stochasticity. By neglecting linkage disequilibria, it yields the joint distribution of allele frequencies and population size on each island. We find that under hard selection, the conditions for local adaptation in a rare habitat are more restrictive for more polygenic traits: even moderate migration load per locus at very many loci is sufficient for population sizes to decline. This further reduces the efficacy of selection at individual loci due to increased drift and because smaller populations are more prone to swamping due to migration, causing a positive feedback between increasing maladaptation and declining population sizes. Our analysis also highlights the importance of demographic stochasticity, which exacerbates the decline in numbers of maladapted populations, leading to population collapse in the rare habitat at significantly lower migration than predicted by deterministic arguments.


2017 ◽  
Author(s):  
Justin D. Yeakel ◽  
Jean P. Gibert ◽  
Peter A. H. Westley ◽  
Jonathan W. Moore

The spatial dispersal of individuals is known to play an important role in the dynamics of populations, and is central to metapopulation theory. At the same time, local adaptation to environmental conditions creates a geographic mosaic of evolutionary forces, where the combined drivers of selection and gene flow interact. Although the dispersal of individuals from donor to recipient populations provides connections within the metapopulation, promoting demographic and evolutionary rescue, it may also introduce maladapted individuals into habitats host to different environmental conditions, potentially lowering the fitness of the recipient population. Thus, dispersal plays a dual role in both promoting and inhibiting local adaptation. Here we explore a model of the eco-evolutionary dynamics between two populations connected by dispersal, where the productivity of each is defined by a trait complex that is subject to local selection. Although general in nature, our model is inspired by salmon metapopulations, where dispersal between populations is defined in terms of the straying rate, which has been shown to be density-dependent, and recently proposed to be shaped by social interactions consistent with collective movement. The results of our model reveal that increased straying between evolving populations leads to alternative stable states, which has large and nonlinear effects on two measures of metapopulation robustness: the portfolio effect and the time to recovery following an induced disturbance. We show that intermediate levels of straying result in large gains in robustness, and that increased habitat heterogeneity promotes robustness when straying rates are low, and erodes robustness when straying rates are high. Finally, we show that density-dependent straying promotes robustness, particularly when the aggregate biomass is low and straying is correspondingly high, which has important ramifications for the conservation of salmon metapopulations facing both natural and anthropogenic disturbances.Media SummaryMany migratory species, such as salmon, are remarkable in finding their way home. This homing has allowed fine-scale adaptations to the environments in which they evolve. But some individuals do not find their way home and instead stray to other locations, especially when there are fewer individuals to help with collective decision-making. With an eco-evolutionary model, we discovered that an intermediate and density-dependent straying rate allows linked populations to be robust to disturbance but maintain local adaptations.


PLoS Genetics ◽  
2021 ◽  
Vol 17 (7) ◽  
pp. e1009652
Author(s):  
Troy N. Rowan ◽  
Harly J. Durbin ◽  
Christopher M. Seabury ◽  
Robert D. Schnabel ◽  
Jared E. Decker

Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent variables to map signatures of selection on complex traits and local adaptation. We identify 207 genomic loci associated with an animal’s birth date, representing ongoing selection for monogenic and polygenic traits. Additionally, hundreds of additional loci are associated with continuous and discrete environments, providing evidence for historical local adaptation. These candidate loci highlight the nervous system’s possible role in local adaptation. While advanced technologies have increased the rate of directional selection in cattle, it has likely been at the expense of historically generated local adaptation, which is especially problematic in changing climates. When applied to large, diverse cattle datasets, these selection mapping methods provide an insight into how selection on complex traits continually shapes the genome. Further, understanding the genomic loci implicated in adaptation may help us breed more adapted and efficient cattle, and begin to understand the basis for mammalian adaptation, especially in changing climates. These selection mapping approaches help clarify selective forces and loci in evolutionary, model, and agricultural contexts.


Author(s):  
Troy N. Rowan ◽  
Harly J. Durbin ◽  
Christopher M. Seabury ◽  
Robert D. Schnabel ◽  
Jared E. Decker

SummarySelection can rapidly drive evolution, especially in stressful environments. We show that novel dependent variables in mixed models with large data sets identify loci responding to polygenic selection and local adaptation. Many techniques identify mutations rapidly selected to high frequencies, based on pronounced signatures in flanking sequences. However, for complex, quantitative traits, selection does not leave these intense sweeps. Instead, in polygenic selection thousands of loci undergo small allele frequency shifts, resulting in large phenotypic changes. Directional selection and local adaptation are actively changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. However, our methods identify 207 loci responding to artificial directional selection, and hundreds more with evidence of local adaptation; with the identified genes highlighting the nervous system’s central role in local adaptation. While advanced technologies increased the rate of directional selection, it has been at the expense of local adaptation, which is especially problematic in changing climates. These selection mapping approaches clarify selective forces and loci in evolutionary, model, and agricultural contexts.


2021 ◽  
Author(s):  
Rachel L Moran ◽  
James B Jaggard ◽  
Emma Y Roback ◽  
Nicolas Rohner ◽  
Johanna E Kowalko ◽  
...  

Compared to selection on new mutations and standing genetic variation, the role of gene flow in generating adaptive genetic variation has been subject to much debate. Theory predicts that gene flow constrains adaptive evolution via natural selection by homogenizing allele frequencies among populations and introducing migrant alleles that may be locally maladaptive. However, recent work has revealed that populations can diverge even when high levels of gene flow are present and that gene flow may play an underappreciated role in facilitating local adaptation by increasing the amount of genetic variation present for selection to act upon. Here, we investigate how genetic variation introduced by gene flow contributes to adaptive evolution of complex traits using an emerging eco-evolutionary model system, the Mexican tetra (Astyanax mexicanus). The ancestral surface form of the Mexican tetra has repeatedly invaded and adapted to cave environments. The Chica cave is unique in that it contains several pool microenvironments inhabited by putative hybrids between surface and cave populations, providing an opportunity to investigate the dynamics of complex trait evolution and gene flow on a local scale. Here we conduct high-resolution genomic mapping and analysis of eye morphology and pigmentation in fish from multiple pools within Chica cave. We demonstrate that hybridization between cave and surface populations contributes to highly localized variation in behavioral and morphological traits. Analysis of sleep and locomotor behaviors between individual pools within this cave revealed reduced sleep associated with an increase in ancestry derived from cave populations, suggesting pool-specific ecological differences may drive the highly-localized evolution of sleep and locomotor behaviors. Lastly, our analyses uncovered a compelling example of convergent evolution in a core circadian clock gene in multiple independent cavefish lineages and burrowing mammals, indicating a shared genetic mechanism underlying circadian disruption in subterranean vertebrates. Together, our results provide insight into the evolutionary mechanisms that promote adaptive genetic variation and the genetic basis of complex behavioral phenotypes involved in local adaptation.


2018 ◽  
Vol 41 ◽  
Author(s):  
Samuel G. B. Johnson

AbstractZero-sum thinking and aversion to trade pervade our society, yet fly in the face of everyday experience and the consensus of economists. Boyer & Petersen's (B&P's) evolutionary model invokes coalitional psychology to explain these puzzling intuitions. I raise several empirical challenges to this explanation, proposing two alternative mechanisms – intuitive mercantilism (assigning value to money rather than goods) and errors in perspective-taking.


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