Feedbacks between species life-history traits and biotic interactions can be critical in determining the impact of climate change on populations. Our research focuses on quantifying these feedbacks in complex natural systems. This research started with the SEASON project.
The video below introduces some of the research.
We are developing and constantly improving simulations to create communities of interacting species from stage-specific or individual demographic rates. We interested in understanding under what conditions (in which types of communities) forecasts of population dynamics and community compositions under climate change fail if they do not account for demography and species interactions. In terms of climate change, we have focused quite a bit on seasonality change.
We have made such multispecies demographic models available as a new module (vignette 6) in the cxr R package for modelling species co-existence.
We are working on including more species and interaction types. See here for detail.
Long-term data on individual or stage-specific demographic rates of several interacting species are rare. And so we work on data integration and developing efficient latent-state approaches to infer demographic rates from abundance datasets for near-term forecasting applications.
We do this work in close collaboration with the Ecological Forecasting Initiative. We are an active part of the new European Chapter of EFI.
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