Testing for adaptation to climate

Latitudinal clines in life history traits observed in common gardens provide strong circumstantial evidence of adaptation to climate on a broad geographic scale in A. thaliana (Stinchcombe et al. 2004. However, to test directly for adaptation to climate, it is necessary to grow genotypes from a large number of populations spanning a range of climates in multiple common gardens across a species’ range, and to measure the fitness of each genotype in each site. Our European field experiments with A. thaliana are, to our knowledge, the first such explicit test of adaptation to climate outside of forestry provenance tests. We can moreover test whether local adaptation to climate is lagging behind rapid recent climate change, an important question for forestry and conservation biology. 

Our data also allow us to dissect the ecological and genetic mechanisms underlying local adaptive evolution. Using genotypic selection analysis and structural equation modeling, we are now elucidating how natural selection acts on specific life history traits in different sites and seasons. Our field data also allow us to measure natural selection at specific loci in different natural environments, using genotypic data from several collaborating laboratories.  We do this by testing for fitness associations with candidate gene polymorphisms in ecotypes (Korves et al. 2007), as well as genomewide scans for fitness-associated SNPs (Fournier-Level et al. 2011).  We can moreover use climate data from the site of ecotype origin to ask whether specific alleles occupy distinct climate niches, using climate envelope analysis tools used by landscape ecologists to predict species range limits (Fournier-Level et al. 2011). We find that entirely different loci are most strongly associated with fitness in each field site. Moreover, the alleles associated with fitness in each site are significantly more differentiated in climate space than genomic controls, suggesting that they may contribute to climatic adaptation. Thus, by combining our field fitness data with climatic information and genomic data for the same ecotypes, we can begin to dissect the underlying genetic mechanisms of local adaptation.