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

快速的人为气候变化正在导致物种分布及其组成的群落发生重大变化。世界森林社区创造了超过7万亿美元的全球国内生产总值，支持了26亿人，但估计显示，超过30%的树种面临灭绝的威胁，在气候变化的情况下，更多的树种濒临灭绝。预测哪些森林将崩溃，哪些社区将在气候变化下最具复原力，对于指导适应性森林管理决策至关重要。然而，理论上的分歧和计算上的挑战阻碍了预测工具的开发，以了解森林和其他系统中的群落形成。利用新技术的组合-包括从功能特征，分层贝叶斯模型和深度学习方法进行社区预测-该项目旨在开发第一个专门设计的社区分布模型。该模型将用于更好地了解其研究系统-温带森林群落-的动态，并对气候变化情景下的群落组成作出一系列预测。这些预测将用于指导旨在管理英国森林社区提供的生态系统服务的保护决策。

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 - temperate 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.