Tackling the challenges of evolutionary forest research with multidata approaches

Many forest tree species have characteristics that make the study of their evolutionary ecology complex. For example, they are long-lived and thus have long generation times, and their often large, complex genomes have hampered establishing genomic resources. One way to tackle this challenge is to access multiple complementary data sources and analytical approaches when attempting to infer patterns of adaptive evolution. In the cover article of this issue of Molecular Ecology, Depardieu et al. (2021) combine large amounts of environmental, genomic, dendrochronological, and gene expression data in a common garden to explore the polygenic basis of drought resistance in white spruce (Picea glauca), a long-lived conifer. They identify candidate genes involved in growth and resistance to extreme drought events and show how multiple data sets may deliver complementary evidence to circumvent the manifold challenges of the research field.