Hosoda Kazufumi, Seno Shigeto, Kamiura Rikuto, Murakami Naomi, Kondoh Michio
RIKEN Center for Biosystems Dynamics Research, 6-2-3 Furuedai, Suita, Osaka 565-0874, Japan.
Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Osaka 565-0871, Japan.
Entropy (Basel). 2023 Dec 5;25(12):1624. doi: 10.3390/e25121624.
The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex post adaptation, typically associated with natural selection, and its proactive counterpart, ex ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified ecosystem stability, (ii) identified correlations between some biodiversity indexes and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, it was suggested that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories-fluctuations, rapid environmental responses, and long-term changes-converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems.
生态系统生物多样性的增加可被视为将能量转化为信息的普遍过程之一,这一过程贯穿于广泛的生命系统。本研究深入探讨了生命系统的动态变化,强调了事后适应(通常与自然选择相关)与其主动对应物事前适应性之间的区别。通过使用合成生态系统的聚结实验,我们(i)量化了生态系统稳定性,(ii)确定了一些生物多样性指数与稳定性之间的相关性,(iii)提出了通过适度的生态系统间相互作用增加生物多样性的机制,以及(iv)推断生态系统的信息载体是物种组成或合并的基因组信息。此外,研究还表明(v)生态系统的变化被限制在一个低维状态空间中,三种不同的变化轨迹——波动、快速环境响应和长期变化——共同汇聚到这个状态空间中。这些发现表明,日常波动可能预示着更广泛的生态系统变化。我们的实验见解,加上从生态系统角度对生命系统信息动态的探索,增强了我们对自然生态系统行为的预测能力,为理解广泛的生命系统提供了一个通用框架。