Wang Xin, Zheng Zhiming, Fu Feng
LMIB, NLSDE, BDBC, PCL and School of Mathematical Sciences, Beihang University, Beijing 100191, People's Republic of China.
Department of Mathematics, Dartmouth College, Hanover, NH 03755, USA.
Proc Math Phys Eng Sci. 2020 Jan;476(2233):20190643. doi: 10.1098/rspa.2019.0643. Epub 2020 Jan 8.
Feedback loops between population dynamics of individuals and their ecological environment are ubiquitously found in nature and have shown profound effects on the resulting eco-evolutionary dynamics. By incorporating linear environmental feedback law into the replicator dynamics of two-player games, recent theoretical studies have shed light on understanding the oscillating dynamics of the social dilemma. However, the detailed effects of more general feedback loops in multi-player games, which are more common especially in microbial systems, remain unclear. Here, we focus on ecological public goods games with environmental feedbacks driven by a nonlinear selection gradient. Unlike previous models, multiple segments of stable and unstable equilibrium can emerge from the population dynamical systems. We find that a larger relative asymmetrical feedback speed for group interactions centred on cooperators not only accelerates the convergence of stable manifolds but also increases the attraction basin of these stable manifolds. Furthermore, our work offers an innovative manifold control approach: by designing appropriate switching control laws, we are able to steer the eco-evolutionary dynamics to any desired population state. Our mathematical framework is an important generalization and complement to coevolutionary game dynamics, and also fills the theoretical gap in guiding the widespread problem of population state control in microbial experiments.
个体种群动态与其生态环境之间的反馈回路在自然界中普遍存在,并对由此产生的生态进化动态产生了深远影响。通过将线性环境反馈定律纳入两人博弈的复制者动态中,最近的理论研究为理解社会困境的振荡动态提供了启示。然而,在多人博弈中更普遍的反馈回路的详细影响,尤其是在微生物系统中更为常见,仍然不清楚。在这里,我们关注由非线性选择梯度驱动的具有环境反馈的生态公共品博弈。与以前的模型不同,种群动态系统中可以出现多个稳定和不稳定平衡段。我们发现,以合作者为中心的群体互动中,更大的相对不对称反馈速度不仅加速了稳定流形的收敛,而且增加了这些稳定流形的吸引域。此外,我们的工作提供了一种创新的流形控制方法:通过设计适当的切换控制定律,我们能够将生态进化动态引导到任何期望的种群状态。我们的数学框架是对协同进化博弈动态的重要推广和补充,也填补了指导微生物实验中普遍存在的种群状态控制问题的理论空白。