On Thursday 17 May, we heard from Professor Jonathan Levine from ETH Zurich, who gave us a fascinating talk that seamlessly wove together ecological theory with its applications, in this case, predicting the consequences of climate change on communities. The occurrence of “novel competitive interactions” between species as they change their distributions is a key prediction of climate change.
However, in Ecology, finding study systems that enable us to test such predictions is challenging, as we attempt to balance realism with the capacity for experimental manipulation. Levine’s group are using alpine meadows, which are naturally arrayed along latitudinal gradients, to study the effects of transplanting communities into different temperature conditions and competitive situations to mimic the outcomes of climate change. This work has shown that the outcomes of competition between plant species may depend on the functional trait similarity of competitors.
The result is that for alpine meadows under climate change, novel competitors may have a greater impact on a focal species when the focal species has failed to migrate, but not when they have advanced their range to higher latitudes. Another challenge is that we are currently unable to accurately predict which species are likely to interact, as evolution over ecological timescales may modify dispersal velocity of different species. Work by Levine’s group using Arabidopsis thaliana as a model species has shown that dispersal over several generations can lead to changes to genotype frequencies, and that this evolution occurs faster in patchier landscapes. Often, when the consequences of climate change are discussed among ecosystem scientists, they are simply described as “unpredictable”. Levine’s group is working to debunk the idea that we cannot predict the results of climate change, by using easily manipulated model systems to test the predictions of community ecology theory.
Elsa is a DPhil student working alongside Professor Andy Hector.