Summary
Genetic association studies in forest tress would greatly benefit from information on tree response to environmental stressors over time. Dendroecology can close this gap by providing such time series measurements. Here, we jointly analyzed dendroecological and genetic data to explore the genetic basis of resistance, recovery and resilience to episodic stress in silver fir.
We used individual level tree-ring data to characterize the growth patterns of surviving silver fir (Abies alba) during the forest dieback in the 1970s and 1980s in Central Europe and associated them with SNPs in candidate genes.
Most trees at our study sites in the Bavarian Forest experienced severe growth decline from 1974 until the mid-1980s, which peaked during the drought year of 1976. Using the machine learning algorithm random forest, we identified 15 candidate genes that were associated with the variance in resistance, resilience and recovery among trees in this period.
With our study we show that the unique possibility of phenotypic time series archived in tree-rings are a powerful resource in genetic association studies. We call for a closer collaboration of dendroceologists and forest geneticists to focus on integrating individual tree level signals in genetic association studies in long lived trees.
