A stochastic field theory for the evolution of quantitative traits in finite populations DOI Creative Commons
Ananda Shikhara Bhat

Theoretical Population Biology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Infinitely many distinct trait values may arise in populations bearing quantitative traits, and modelling their population dynamics is thus a formidable task. While classical models assume fixed or infinite size, which the total size fluctuates due to demographic noise births deaths can behave qualitatively differently from constant density-dependent dynamics. In this paper, I present stochastic field theory for eco-evolutionary of finite one-dimensional traits. derive equations that describe evolution densities, frequencies, mean value any population. These recover well-known results such as replicator-mutator equation, Price gradient limit. For populations, intricate interplay between natural selection, noise-induced feedback, neutral genetic drift determining evolutionary trajectories. My methods use ideas statistical physics, calculus variations, SPDEs, providing alternative complement measure-theoretic martingale approach more common literature.

Language: Английский

The interplay of trophic interactions and game dynamics gives rise to life-history trade-offs, consistent personalities, and predator–prey and aggression power laws DOI Creative Commons
Mohammad Salahshour

New Journal of Physics, Journal Year: 2025, Volume and Issue: 27(2), P. 023009 - 023009

Published: Feb. 1, 2025

Abstract Ecological processes and evolutionary change are increasingly recognized as intimately linked. Here, we introduce an eco-evolutionary model of trophic interactions between predators prey show that the flow resources in ecosystem results scale-invariant spatial temporal structure ecosystems. In contrast to conventional approaches rely on fitness-based selection, evolution our framework is a direct consequence ecological interactions. To illustrate this, combine with games by allowing individuals play game within population where they can adopt aggressive or non-aggressive strategies. We develop consistent personalities their life-history trade-offs become intertwined dynamics. Aggressive tend live faster, more reproduction-focused lives, whereas nonaggressive favor slower, longer-lived These patterns emerge naturally, rather than being imposed assumptions. Furthermore, demonstrate nonequilibrium dynamics resource decisive role driving across populations. identify new class aggression scaling laws arising from interplay processes. The relates predator–prey food web control shows small offspring size, high relative mobility, low predator conversion efficiency, competition, competition all over web. Our findings illuminate how large-scale patterns—including power biomass avalanche-like pulses—can relate outcomes such personalities, trade-offs, density-dependent growth. This perspective strengthens emerging view ecology two faces same coin, each shaping other self-organized, energy-driven system.

Language: Английский

Citations

0

A stochastic field theory for the evolution of quantitative traits in finite populations DOI Creative Commons
Ananda Shikhara Bhat

Theoretical Population Biology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Infinitely many distinct trait values may arise in populations bearing quantitative traits, and modelling their population dynamics is thus a formidable task. While classical models assume fixed or infinite size, which the total size fluctuates due to demographic noise births deaths can behave qualitatively differently from constant density-dependent dynamics. In this paper, I present stochastic field theory for eco-evolutionary of finite one-dimensional traits. derive equations that describe evolution densities, frequencies, mean value any population. These recover well-known results such as replicator-mutator equation, Price gradient limit. For populations, intricate interplay between natural selection, noise-induced feedback, neutral genetic drift determining evolutionary trajectories. My methods use ideas statistical physics, calculus variations, SPDEs, providing alternative complement measure-theoretic martingale approach more common literature.

Language: Английский

Citations

1