Resilient treescapes for a changing climate: a mathematical approach

气候变化预计将导致全球范围内偏离当前的森林密度和物种分布。同时，长期天气模式的预测扭曲将通过提供有利的生存条件来鼓励病原体成功入侵。这两个因素结合在一起，构成了对地球森林及其所支持的丰富生物多样性的紧迫威胁。为了确保在气候变化的情况下树枝逃生的生存，世界各国政府需要强大的工具来支持对假想的未来入侵的预测和管理。这个项目试图探索有效和经济的策略来建造适应气候变化的树枝逃生。我们将通过构建一个密度相关的树木病害传播的时空随机波前模型并将该模型推广到全国范围来实现这一点。我们将把预测的变化纳入树木分布，并使用该模型来预测面对气候变化的长期疾病传播。特别是，我们将重点关注橡树进程蛾在英国的传播。最后，我们将整合缓解策略并使用我们的模型进行场景测试。该项目的主要目的是了解气候变化对树生疾病传播的影响，并就如何随着气候变化的进展最好地管理英国的疾病爆发向DEFRA等机构提供建议。我们的进展可以根据五个目标进行评估：1)构建一个复杂的树木病害传播的时空模型。2)利用该模型预测OPM何时达到无虫害边界。3)将模型扩展到全国范围。4)在面对气候变化的情况下，确定OPM的长期传播。5)确定缓解/干预策略的可行性。

Climate change is expected to lead to worldwide deviations from current forest densities and species distributions. Simultaneously, the predicted distortions in long-term weather patterns will encourage successful pathogen invasion by providing favourable conditions for survival. These two factors combine into an urgent threat to Earth's forests and the rich biodiversity they support. To ensure the survival of treescapes in the face of climate change, world governments require robust tools to support the prediction and management of hypothetical future invasions.This project seeks to explore effective and economical strategies for building climate-resilient treescapes. We will achieve this by constructing a density-dependent, spatio-temporal stochastic wavefront model of tree disease spread and extending the model to a national scale. We will incorporate predicted changes to tree distributions and use the model to predict long-term disease spread in the face of climate change. In particular, we will focus on the spread of Oak Processionary Moth in the UK. Finally, we will incorporate mitigation strategies and use our model for scenario testing. The primary aims of the project are to understand the effect of climate change on arboreal disease propagation and to advise agencies such as DEFRA on how best to manage disease outbreaks in the UK as climate change progresses. Our progress can be assessed against five objectives:1) Construct a sophisticated spatio-temporal model of tree disease propagation. 2) Use the model to predict when OPM will reach pest-free boundaries.3) Expand the model to a national scale.4) Determine long term spread of OPM in the face of climate change. 5) Determine viability of mitigation/intervention strategies.