Periodic Reporting for period 4 - NICH (Novel interactions and species’ responses to climate change)
Reporting period: 2020-08-01 to 2021-12-31
Ecologists today are challenged by the need to predict how species, communities and ecosystems respond to global climate change. Key sources of uncertainty are how these responses might be modified by evolution and by changes to species interactions. As well as altering interactions among species that already co-occur in communities today, climate change is leading to the large-scale reshuffling of species distributions, giving rise to novel interactions among species that did not previously co-occur. However, the ecological and evolutionary consequences of novel interactions remain poorly understood. The overarching goal of this project was to implement cutting-edge experiments and modeling approaches to address three questions about the impact of novel competitors on responses to climate change in alpine plant communities: (1) How will novel interactions impact alpine plant responses to climate change? We tested the ecological consequences of novel competitors for population persistence, and investigated 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 tested 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 aimed to parameterize process-based species distribution models with our experimental data, to explore the consequences of changing competitive interactions for range dynamics under climate change. The project concludes that novel competitors specifically, and changing species interactions more generally, often play a key role in delimiting species ranges and shaping their ecological and evolutionary responses to changing climate.
We established several large-scale field experiments to study different aspects of plant responses to changing climate and competitive interactions. Using a whole-community transplant experiment across an elevation gradient combined with demographic modelling (WP1), we showed that novel competitors accelerate rates of local extinction of alpine plants under climate change, which can be decisive under low amounts of warming, helping to explain why we see “extinction debt” in alpine ecosystems up to now (Nomoto & Alexander, 2021). Using this experiment, we performed selection analyses and estimated trait heritability to explore evolutionary implications of changing competition and climate. We found that warming can impose selection on alpine plant traits, but that competitors generally constrain selection, and in some cases reduce evolvability, suggesting that evolutionary rescue is unlikely to occur in our study species (Nomoto et al., two articles in prep.). We also expanded WP1 to study novel plant-soil interactions under climate change (Cardinaux et al. 2018, Hagedorn et al. 2019, Walker et al. 2021).
We established a separate field experiment (WP2) at three elevations to investigate whether species’ traits predict the population-level outcome of pairwise competitive interactions measured on 14 lowland and alpine species. We found that competition shapes upper as well as lower elevation range limits in this system (Lyu & Alexander 2022), and that this is mainly due to impacts of competitors on plant growth. Nonetheless, functional traits were in general not strong predictors of interactions between either current or novel competitors. We therefore developed alternative modeling approaches to study species’ ranges and their dynamics (WP3), including occupancy models, evolutionary functional-structural plant models, Bayesian non-linear distribution models (Bramon Mora et al., in revision), metacommunity models (Alexander et al. 2018) and evolutionary trade-off models (Alexander et al. 2022). We also reviewed how positive biotic interactions shape range limits (Stephan et al. 2021) and outlined challenges and opportunities to link community ecology and marcoecology (Alexander et al. 2016; Wüest et al. 2019, Guisan et al. 2019).
So far, the project has led to 15 publications, with several others currently in prep. or review, involved 13 student projects from bachelor to PhD levels, and been represented in over 30 seminars or presentations and numerous public events.
We established a separate field experiment (WP2) at three elevations to investigate whether species’ traits predict the population-level outcome of pairwise competitive interactions measured on 14 lowland and alpine species. We found that competition shapes upper as well as lower elevation range limits in this system (Lyu & Alexander 2022), and that this is mainly due to impacts of competitors on plant growth. Nonetheless, functional traits were in general not strong predictors of interactions between either current or novel competitors. We therefore developed alternative modeling approaches to study species’ ranges and their dynamics (WP3), including occupancy models, evolutionary functional-structural plant models, Bayesian non-linear distribution models (Bramon Mora et al., in revision), metacommunity models (Alexander et al. 2018) and evolutionary trade-off models (Alexander et al. 2022). We also reviewed how positive biotic interactions shape range limits (Stephan et al. 2021) and outlined challenges and opportunities to link community ecology and marcoecology (Alexander et al. 2016; Wüest et al. 2019, Guisan et al. 2019).
So far, the project has led to 15 publications, with several others currently in prep. or review, involved 13 student projects from bachelor to PhD levels, and been represented in over 30 seminars or presentations and numerous public events.
This project has significantly advanced our understanding of how plants respond to climate change, showing that changing competitive interactions can sometimes drive local population declines under warming. Our innovative field experiments combined with detailed demographic modelling have also led to new fundamental insights into how plant-plant interactions vary across environmental gradients, showing that competition can shape both upper and lower elevation limits of plants. Together, these findings go beyond the current state-of-the-art by providing experimental tests of the mechanisms through which species interactions affect climate change extinction debt and species’ range limits. Furthermore, our experiments have yielded novel insights into how competition influences evolutionary potential under changing climate. We have found that competition can constrain natural selection acting on alpine plants as climate warms, making it unlikely that evolution will rescue populations of the species we studied that are threatened by both changing climate and changing competitive interactions. This work has highlighted the importance of community context (i.e. biotic interactions) for the potential of species to evolve under changing climate, including on adaptive potential at species range edges. Finally, we have developed new tools for studying species’ ranges and their dynamics, including multispecies Bayesian non-linear distribution models that combine expert knowledge and distribution data, and mechanistic models to study how climate and biotic interactions shape plant population adaptation. Overall, the project has laid a foundation for studying impacts of novel interactions under changing climate, and has showcased how understanding and predicting climate change impacts on natural communities requires an interdisciplinary approach bridging community-, evolutionary- and macroecology.