Experimental migration upward in elevation is associated with strong selection on life history traits

One of the strongest biological impacts of climate change has been the movement of species poleward and upward in elevation. Yet, what is not clear is the extent to which the spatial distribution of locally adapted lineages and ecologically important traits may also shift with continued climate change. Here, we take advantage of a transplant experiment mimicking up‐slope seed dispersal for a suite of ecologically diverse populations of yellow monkeyflower (Mimulus guttatus sensu lato) into a high‐elevation common garden during an extreme drought period in the Sierra Nevada mountains, California, USA. We use a demographic approach to quantify fitness and test for selection on life history traits in local versus lower‐elevation populations and in normal versus drought years to test the potential for up‐slope migration and phenotypic selection to alter the distribution of key life history traits in montane environments. We find that lower‐elevation populations tend to outperform local populations, confirming the potential for up‐slope migration. Although selection generally favored some local montane traits, including larger flowers and larger stem size at flowering, drought conditions tended to select for earlier flowering typical of lower‐elevation genotypes. Taken together, this suggests that monkeyflower lineages moving upward in elevation could experience selection for novel trait combinations, particularly under warmer and drier conditions that are predicted to occur with continued climate change. We use a high‐elevation common garden experiment to test the potential for up‐slope migration and corresponding patterns of phenotypic selection in yellow monkeyflowers. We find that lower‐elevation populations have higher fitness than local populations, but experience strong selection on life history traits in a high‐elevation environment. Lineages moving upward in elevation with continued climate change could experience selection for novel trait combinations.