Bring in the genes: genetic-ecophysiological modeling of the adaptive response of trees to environmental change. With application to the annual cycle - Kramer, Koen; van der Werf, Bert; Schelhaas, Mart-Jan (Frontiers in Plant Science, 2015)
The observation of strong latitudinal clines in the date of bud burst of tree species indicate that populations of these species are genetically adapted to local environmental conditions. Existing phenological models rarely address this clinal variation, so that adaptive responses of tree populations to changes in environmental conditions are not taken into account, e.g. in models on species distributions that use phenological sub-models. This omission of simulating adaptive response in tree models may over- or underestimate the effects of climate change on tree species distributions, as well as the impacts of climate change on tree growth and productivity. Here, we present an approach to model the adaptive response of traits to environmental change based on an integrated process-based eco-physiological and quantitative genetic model of adaptive traits. Thus, the parameter values of phenological traits are expressed in genetic terms (allele effects and - frequencies, number of loci) for individual trees. These individual trees thereby differ in their ability to acquire resources, grow and reproduce as described by the process-based model, leading to differential survival. Differential survival is thus the consequence of both differences in parameters values and their genetic composition. By simulating recombination and dispersal of pollen, the genetic composition of the offspring will differ from that of their parents. Over time, the distribution of both trait values and the frequency of the underlying alleles in the population change as a consequence of changes in environmental drivers leading to adaptation of trees to local environmental conditions. This approach is applied to an individual-tree growth model that includes a phenological model on the annual cycle of trees whose parameters are allowed to adapt. An example of the adaptive response of the onset of the growing season across Europe is presented.