On the importance of time scales when studying adaptive evolution

Long-term field studies coupled with quantitative genomics offer a powerful means to understand the genetic bases underlying quantitative traits and their evolutionary changes. However, analyzing and interpreting the time scales at which adaptive evolution occurs is challenging. First, while evolution is predictable in the short term, with strikingly rapid phenotypic changes in data series, it remains unpredictable in the long term. Second, while the temporal dynamics of some loci with large effect on phenotypic variation and fitness have been characterized, this task can be complicated in cases of highly polygenic trait architecture implicating numerous small effect size loci, or when statistical tests are sensitive to the heterogeneity of some key characteristics of the genome, like recombination rate variations. After introducing these aforementioned challenges, we discuss a recent investigation of the genomic architecture and spatio-temporal variation in great tit bill length, which was related to the recent use of bird feeders. We discuss how this case study illustrates the importance of considering different temporal scales and evolutionary mechanisms both while analyzing trait temporal trends and when searching for and interpreting the signals of putative genomic footprints of selection. More generally this commentary discusses interesting challenges for unraveling the time scale at which adaptive traits evolve and their genomic bases.\n\nImpact summaryAn important goal in evolutionary biology is to understand how individual traits evolve, leading to fascinating variations in time and space. Long-term field studies have been crucial in trying to understand the timing, extent, and ecological determinants of such trait variation in wild populations. In this context, recent genomic tools can be used to look for the genetic bases underlying such trait variation and can provide clues on the nature and timing of their evolution. However, the analysis and the interpretation of the time scales at which evolution occurs remain challenging. First, analyzing long-term data series can be tricky; short-term changes are highly predictable whereas long-term evolution is much less predictable. A second difficult task is to study the architecture of complex quantitative traits and to decipher the timing and roles of the several genomic mechanisms involved in their evolution. This commentary introduces these challenges and discusses a recent investigation of the nature and timing of ecological and genomic factors responsible for variation in great tit bill length. Overall, we raise cautionary warnings regarding several conceptual and technical features and limitations when coupling analyses of long-term and genomic data to study trait evolution in wild populations.