Disentangling the environmentally induced and stochastic developmental components of phenotypic variation

Abstract The phenotypic variation in populations is the result of genetic variation and two nongenetic sources of variation, namely, environmentally induced variation (EIV) and stochastic developmental variation (SDV). EIV (phenotypic plasticity sensu stricto) and SDV (developmental noise) occur in all kingdoms of life and are thus considered general biological principles. They have in common that they are mediated by epigenetic mechanisms but they differ in quality and function. EIV is directional and contributes to phenotype optimization in the inhabited environment, whereas SDV is random and contributes to evolutionary bet-hedging. This chapter discusses the differences and relationships between EIV and SDV on a theoretical and empirical basis and presents examples on their extent in animals, the most complex organisms on earth. In the laboratory, EIV and SDV were determined by exposing genetically identical populations to either different or single environments. The rare studies on the determination of EIV and SDV in natural populations exploited clonal lineages adapted to different environments. Computer simulation of phenotypes produced by reaction-diffusion mechanisms has also proven useful for determining the extent of SDV. The available data indicate that a surprisingly high proportion of phenotypic variation is caused by nongenetic sources. The relative contribution of EIV and SDV to phenotypic variation depends on species, trait, and environment and is apparently subject to evolutionary change. There is increasing evidence that alterations of the methylation marks on the DNA and acetylation and methylation marks on the histones are among the molecular mechanisms that produce different phenotypes from the same genome, either stochastically or by environmental induction. The monoclonal marbled crayfish, which in recent times has adapted to diverse freshwater habitats on three continents despite genetic identity, is introduced as a promising model to investigate the extent and molecular underpinning of EIV and SDV and their ecological and evolutionary relevance in depth.