Periodic Reporting for period 3 - NICH (Novel interactions and species’ responses to climate change)
Reporting period: 2019-02-01 to 2020-07-31
(1) How will novel interactions impact species’ responses to climate change? We are testing the ecological consequences of novel competitors for population persistence, and the potential for longer-term evolutionary responses, by transplanting whole plant communities across elevation gradients to simulate future competitive scenarios faced by focal alpine plants.
(2) Do species traits predict the outcome of novel interactions? A mechanistic understanding of competitive effects is essential to predict impacts of novel interactions. We are testing how climate affects the outcome of competition among pairs of species planted along an elevation climate gradient, and whether these effects can be predicted using species’ functional traits.
(3) What are the implications of novel competitive interactions for species’ ranges dynamics under climate change? We will use process-based species distribution models, parameterized with our experimental data, to explore the consequences of changing competitive interactions for range dynamics under climate change.
This project will advance our understanding of species’ responses to climate change, and develop approaches that can be applied to a diversity of other ecological settings. It also tackles fundamental questions in ecology, shedding light on the mechanisms shaping species distributions. By linking experimental community ecology and biogeography, the project pushes the limits of our ability to predict the dynamics of complex ecological systems.
In a controlled glasshouse experiment we investigated the potential effects of changing plant-soil biota interactions, which arise as species migrate to higher elevation with climate change, on the coexistence of novel plant competitors. Our results revealed positive effects of low elevation soil biota on plant performance, but with only one exception the soil biota effects did not alter model predictions for the qualitative outcome of competition between high and low elevation plant species (Cardinaux et al., 2018). We used the field experiment to investigate consequences of novel interactions for ecosystem processes. Our preliminary results suggest that low elevation plants colonizing alpine communities can modify effects of climate warming on components of the soil carbon cycle, at least in the short term (Walker et al., in review). In a review article, we place these effects of novel species within the wider context of how above- and belowground linkages are affecting vegetation responses to climate change in mountains (Hagedorn et al., 2019).
We set-up a second large-scale field experiment to address Question 2. In this experiment we compete 14 plant species from high and low elevation in pairwise combinations in three sites at low, intermediate and high elevation, and collect data on their performance and functional traits. We are testing how the outcome of these interactions varies with climate, and the extent to which the outcome of competition can be predicted by species’ functional traits. So far we have collected and are analysing data from the first growing season. We also plan to use these data to develop models that address Question 3.
The important role that species interactions play in mediating effects of climate within ecological communities poses great challenges for forecasting responses of biodiversity, and in particular species’ distributions, to climate change. We published an article that lays-out the need for experiments that quantify outcomes of novel interactions in ways that can inform species distribution models, and outlines a research agenda to achieve this goal (Alexander et al. 2016). Furthermore, to provide a baseline for our empirical research we synthesised current knowledge about the mechanisms affecting disequilibrium range dynamics in mountain ecosystems. We published a review paper on this topic (Alexander et al. 2018), where we also developed a mechanistic community model of disequilibrium range dynamics across elevation gradients, providing a baseline for the models that will be used to address Question 3.