Understanding biotic responses to global change: Local adaptation and its genetic architecture
Decades of common garden experimentation have revealed that populations of forest trees are adapted to their local site conditions. Missing from these studies, however, are the identification and characterization of the genetic components conferring the observable fitness differences among trees. Previous studies using small sets of candidate genes to characterize genotype-phenotype maps for forest trees yielded promising results, although these studies often ignored the environmental and ecological context of these maps. Much of the genetic variation documented in common garden experimentation, however, remains unexplained. Here, we utilized genomic and phenotypic data derived from common gardens for five species of conifers (Pinus albicaulis Engelm., P. balfouriana Grev. & Balf., Pinus lamberitana Dougl., P. monticola Dougl. ex D. Don, and P. taeda L.) to identify and describe components of the genetic architecture underlying locally adapted phenotypes.
Our results confirmed that tree populations are adapted to local site conditions, even at relatively fine spatial scales. For example, height growth and carbon isotope ratios were significantly more differentiated (QST) among populations of P. monticola distributed across the Lake Tahoe Basin of California and Nevada than were allele frequencies for a set of molecular markers (FST). We generated lists of candidate regions affecting quantitative traits for each focal species using genotype-phenotype, as well as genotype-environment, correlations. Several instances of the same gene affecting the same trait in different species were noted. Lastly, we leveraged these results to test the hypothesis that for recently diverged populations local adaptation is expected to emerge as a consequence of multilocus interactions that are partitioned among populations. Using a novel method based on both population and quantitative genetic methodologies, we show that this hypothesis is well supported at the spatial scale of the Lake Tahoe Basin, as well as at the spatial scale of the entire range for P. taeda. Our results are relevant to modeling biotic responses to global change, as the spatial distribution of genotypes within and among populations affects responses at the level of species.