Community Distribution Modelling: Predicting how UK forest communities will respond to climate change.

Rapid anthropogenic climate change is causing significant shifts in the distribution of species and the communities they compose. The world's forest communities generate more than $7 trillion of global Gross Domestic Product and support 2.6 billion people, however estimates show that more than 30% of tree species are threatened with extinction with many more endangered under climate change scenarios. Predicting which forests will collapse and which communities will be most resilient under climate change is crucial for guiding adaptive forest management decisions. However, theoretical disagreement and computational challenges have hindered the development of predictive tools for understanding community formation in forests and other systems. Utilising a combination of novel techniques - including community prediction from functional traits, hierarchical Bayesian models and deep learning methods - this project aims to develop the first purpose-designed community distribution model. This model will be used to better understand the dynamics of its study system - UK forest communities - and to make a series of predictions about community composition under climate change scenarios. These predictions will be used to guide conservation decisions aimed at stewarding the ecosystem services provided by the UK's forest communities.