PT - JOURNAL ARTICLE AU - Jack M. Colicchio AU - Jacob Herman TI - Empirical patterns of environmental variation favor the evolution of adaptive transgenerational plasticity AID - 10.1101/426007 DP - 2019 Jan 01 TA - bioRxiv PG - 426007 4099 - http://biorxiv.org/content/early/2019/10/08/426007.short 4100 - http://biorxiv.org/content/early/2019/10/08/426007.full AB - Effects of parental environment on offspring traits have been well known for decades. Interest in this transgenerational form of phenotypic plasticity has recently surged due to advances in our understanding of its mechanistic basis. Theoretical research has simultaneously advanced by predicting the environmental conditions that should favor the adaptive evolution of transgenerational plasticity. Yet whether such conditions actually exist in nature remains largely unexplored. Here, using long-term climate data, we modeled optimal levels of transgenerational plasticity for an organism with a one-year life cycle at a spatial resolution of 4km2 across the continental US. Both annual temperature and precipitation levels were often autocorrelated, but the strength and direction of these autocorrelations varied considerably across the continental US and even among nearby sites. When present, such environmental autocorrelations render offspring environments statistically predictable based on the parental environment, a key condition for the adaptive evolution of transgenerational plasticity. Results of our optimality models were consistent with this prediction: high levels of transgenerational plasticity were favored at sites with strong environmental autocorrelations, and little-to-no transgenerational plasticity was favored at sites with weak or non-existent autocorrelations. These results are among the first to show that natural patterns of environmental variation favor the evolution of adaptive transgenerational plasticity. Furthermore, these findings suggest that transgenerational plasticity is highly variable in nature, depending on site-specific patterns of environmental variation.