The importance of biotic interactions and local adaptation for plant response to environmental changes: field evidence along an elevational gradient

Predicting the response of species to environmental changes is a great and on-going challenge for ecologists, and this requires a more in-depth understanding of the importance of biotic interactions and the population structuration in the landscape. Using a reciprocal transplantation experiment, we tested the response of five species to an elevational gradient. This was combined to a neighbour removal treatment to test the importance of local adaptation and biotic interactions. The trait studied was performance measured as survival and biomass. Species response varied along the elevational gradient, but with no consistent pattern. Performance of species was influenced by environmental conditions occurring locally at each site, as well as by positive or negative effects of the surrounding vegetation. Indeed, we observed a shift from competition for biomass to facilitation for survival as a response to the increase in environmental stress occurring in the different sites. Unlike previous studies pointing out an increase of stress along the elevation gradient, our results supported a stress gradient related to water availability, which was not strictly parallel to the elevational gradient. For three of our species, we observed a greater biomass production for the population coming from the site where the species was dominant (central population) compared to population sampled at the limit of the distribution (marginal population). Nevertheless, we did not observe any pattern of local adaptation that could indicate adaptation of populations to a particular habitat. Altogether, our results highlighted the great ability of plant species to cope with environmental changes, with no local adaptation and great variability in response to local conditions. Our study confirms the importance of taking into account biotic interactions and population structure occurring at local scale in the prediction of communities’ responses to global environmental changes.