Epigenetic Memory as Adaptive Architecture in Fluctuating Environments: A Hybrid Regime Model Linking Environmental Controllability, Genomic Addressability, and Long-Term Evolution

Transgenerational epigenetic inheritance (TEI) and transgenerational plasticity are well documented in plants and some invertebrates, yet appear weak, transient, or mechanistically constrained in mammals. Existing theory has established that transgenerational effects are favored primarily when environmental cues are reliable and parental and offspring environments are positively autocorrelated, typically under intermediate rates of environmental change. However, current accounts often treat epigenetic inheritance, phenotypic switching, and within-generation plasticity as distinct strategies rather than as interacting layers within a unified adaptive architecture. Here, I propose a hybrid regime model in which epigenetic memory operates as a continuous regulatory process within discrete adaptive regimes, with regime shifts triggering reconfiguration of retention, reset, and weighting of epigenetic states. The framework integrates results from models of anticipatory effects, stochastic switching in fluctuating environments, and niche construction theory, and introduces environmental controllability as a key determinant of when biological transgenerational memory is selectively favored. A central claim is that epigenetic memory is constrained by genomic addressability: DNA sequence and chromatin architecture define where epigenetic states can be established, how stable they can be, and how readily they can be erased. The model yields testable predictions regarding when epigenetic inheritance should be strongest—namely, under limited environmental controllability, intermediate environmental correlation times, and genomic architectures that support stable yet resettable epigenetic states. Importantly, the framework clarifies that long-term evolution acts not on epigenetic states themselves, but on the genetic architecture that tunes epigenetic capacity. This reframes epigenetic inheritance as an optimized, bounded component of adaptive systems rather than an open-ended alternative to genetic evolution.