Learning mitigates genetic drift
| Autoři | |
|---|---|
| Rok publikování | 2022 |
| Druh | Článek v odborném periodiku |
| Časopis / Zdroj | Nature Scientific Reports |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | https://www.nature.com/articles/s41598-022-24748-8 |
| Doi | http://dx.doi.org/10.1038/s41598-022-24748-8 |
| Klíčová slova | EFFECTIVE POPULATION-SIZE; EVOLUTION |
| Přiložené soubory | |
| Popis | Genetic drift is a basic evolutionary principle describing random changes in allelic frequencies, with far-reaching consequences in various topics ranging from species conservation efforts to speciation. The conventional approach assumes that genetic drift has the same effect on all populations undergoing the same changes in size, regardless of different non-reproductive behaviors and history of the populations. However, here we reason that processes leading to a systematic increase of individuals` chances of survival, such as learning or immunological memory, can mitigate loss of genetic diversity caused by genetic drift even if the overall mortality rate in the population does not change. We further test this notion in an agent-based model with overlapping generations, monitoring allele numbers in a population of prey, either able or not able to learn from successfully escaping predators' attacks. Importantly, both these populations start with the same effective size and have the same and constant overall mortality rates. Our results demonstrate that even under these conditions, learning can mitigate loss of genetic diversity caused by drift, by creating a pool of harder-to-die individuals that protect alleles they carry from extinction. Furthermore, this effect holds regardless if the population is haploid or diploid or whether it reproduces sexually or asexually. These findings may be of importance not only for basic evolutionary theory but also for other fields using the concept of genetic drift. |
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