Realistic fitness landscapes generally display a redundancy-fitness trade-off: highly fit trait configurations are inevitably rare, while less fit trait configurations are expected to be more redundant. The resulting sub-optimal patterns in the fitness distribution are typically described by means of effective formulations, where redundancy provided by the presence of neutral contributions is modelled implicitly, e.g. with a bias of the mutation process. However, the extent to which effective formulations are compatible with explicitly redundant landscapes is yet to be understood, as well as the consequences of a potential miss-match. Here we investigate the effects of such trade-off on the evolution of phenotype-structured populations, characterised by continuous quantitative traits. We consider a typical replication-mutation dynamics, and we model redundancy by means of two dimensional landscapes displaying both selective and neutral traits. We show that asymmetries of the landscapes will generate neutral contributions to the marginalised fitness-level description, that cannot be described by effective formulations, nor disentangled by the full trait distribution. Rather, they appear as effective sources, whose magnitude depends on the geometry of the landscape. Our results highlight new important aspects on the nature of sub-optimality. We discuss practical implications for rapidly mutant populations such as pathogens and cancer cells, where the qualitative knowledge of their trait and fitness distributions can drive disease management and intervention policies.

现实的适应度景观通常表现出冗余-适应度的权衡：高度拟合的特征配置不可避免地很少见，而不太适应的特征配置预计会更加冗余。适应度分布中产生的次优模式通常通过有效的公式来描述，其中由中性贡献的存在提供的冗余被隐式建模，例如。G. 带有变异过程的偏差。然而，有效的公式与明确冗余的景观相容的程度还有待了解，以及潜在的错配的后果。在这里，我们研究了这种权衡对表型结构种群进化的影响，其特征是连续的数量性状。我们考虑了典型的复制突变动态，我们通过显示选择性和中性特征的二维景观来模拟冗余。我们表明，景观的不对称性将对边缘化的适应度水平描述产生中性贡献，这无法通过有效的公式来描述，也无法通过完整的特征分布来解开。相反，它们似乎是有效的来源，其大小取决于景观的几何形状。我们的结果突出了次优性质的新重要方面。我们讨论了病原体和癌细胞等快速突变种群的实际意义，在这些种群中，对它们的性状和适应度分布的定性知识可以推动疾病管理和干预政策。