Taming fitness: Organism‐environment interdependencies preclude long‐term fitness forecasting,BioEssays

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Taming fitness: Organism‐environment interdependencies preclude long‐term fitness forecasting
BioEssays ( IF 3.2 ) Pub Date : 2020-11-25 , DOI: 10.1002/bies.202000157
Guilhem Doulcier ₁ , Peter Takacs ₁ , Pierrick Bourrat _{1,

2}

Affiliation

Fitness is a central but notoriously vexing concept in evolutionary biology. The propensity interpretation of fitness is often regarded as the least problematic account for fitness. It ties an individual's fitness to a probabilistic capacity to produce offspring. Fitness has a clear causal role in evolutionary dynamics under this account. Nevertheless, the propensity interpretation faces its share of problems. We discuss three of these. We first show that a single scalar value is an incomplete summary of a propensity. Second, we argue that the widespread method of “abstracting away” environmental idiosyncrasies by averaging over reproductive output in different environments is not a valid approach when environmental changes are irreversible. Third, we point out that expanding the range of applicability for fitness measures by averaging over more environments or longer time scales (so as to ensure environmental reversibility) reduces one's ability to distinguish selectively relevant differences among individuals because of mutation and eco‐evolutionary feedbacks. This series of problems leads us to conclude that a general value of fitness that is both explanatory and predictive cannot be attained. We advocate for the use of propensity‐compatible methods, such as adaptive dynamics, which can accommodate these difficulties.

中文翻译：

驯服适应度：生物体与环境的相互依赖性妨碍了长期适应度预测

适应性是进化生物学中一个核心但众所周知的令人烦恼的概念。适应度的倾向解释通常被认为是适应度问题最少的解释。它将个体的适应性与产生后代的概率能力联系起来。在这种情况下，适应度在进化动力学中具有明显的因果作用。然而，倾向解释面临着它的部分问题。我们讨论其中三个。我们首先表明，单个标量值是对倾向的不完整总结。其次，我们认为，当环境变化不可逆转时，通过平均不同环境中的生殖产出来“抽象掉”环境特质的广泛方法不是有效的方法。第三，我们指出，通过在更多环境或更长的时间尺度上进行平均（以确保环境可逆性）来扩大适应度测量的适用范围会降低人们因突变和生态进化反馈而选择性区分个体之间相关差异的能力。这一系列问题使我们得出结论，无法获得既具有解释性又具有预测性的适应度的一般值。我们提倡使用倾向兼容的方法，例如自适应动力学，可以解决这些困难。这一系列问题使我们得出结论，无法获得既具有解释性又具有预测性的适应度的一般值。我们提倡使用倾向兼容的方法，例如自适应动力学，可以解决这些困难。这一系列问题使我们得出结论，无法获得既具有解释性又具有预测性的适应度的一般值。我们提倡使用倾向兼容的方法，例如自适应动力学，可以解决这些困难。

更新日期：2020-12-22

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