Department of Plant and Environmental Sciences, Weizmann Institute of Science, Herzl Street 234, Rehovot 7610001, Israel.
Santa Fe Institute, Santa Fe, NM, USA.
J Theor Biol. 2021 Oct 21;527:110819. doi: 10.1016/j.jtbi.2021.110819. Epub 2021 Jun 26.
To be able to deal with uncertainty is of primary importance to most living organisms. When cues provide information about the state of the environment, organisms can use them to respond flexibly. Life forms have evolved complex adaptations and sensory mechanisms to use these environmental cues and extract valuable information about the environment. Previous work has shown a theoretical limit to the amount of fitness benefit possible to be extracted from the cues. We show that the previously used information theoretical approaches can be generalised to scenarios involving any potential relationship between the number of possible phenotypes and environmental states. Such cases are relevant when physiological constraints or complex ecological scenarios lead to the number of environmental states exceeding potential phenotypes. We illustrate cases in which these scenarios can emerge: along environmental gradients, such as geographical transects or complex environments, where organisms adopt different bet-hedging strategies, switching stochastically between phenotypes or developing intermediate ones. In conclusion, we develop an information-theoretic extensible approach for investigating and quantifying fitness in ecological studies.
能够应对不确定性对大多数生物来说至关重要。当线索提供有关环境状态的信息时，生物体可以利用这些线索灵活地做出反应。生命形式已经进化出复杂的适应和感觉机制，以利用这些环境线索并从中提取有关环境的有价值信息。先前的工作表明，从线索中提取可能的适应性收益存在理论上的限制。我们表明，先前使用的信息理论方法可以推广到涉及可能的表型数量与环境状态之间任何潜在关系的情况。当生理限制或复杂的生态场景导致环境状态数量超过潜在表型时，就会出现这种情况。我们举例说明了可能出现这些情况的情况：沿着环境梯度，例如地理横断或复杂的环境，其中生物体采用不同的风险分散策略，在表型之间随机切换或发展中间表型。总之，我们开发了一种信息论可扩展的方法，用于研究和量化生态研究中的适应性。
