Modelling butterfly abundance at varying spatial scales to inform conservation delivery

在过去的40年里，英国四分之三的蝴蝶物种已经减少。蝴蝶对栖息地和气候变化反应迅速，因此它们的种群状况是一个有价值的生物多样性指标。对长期蝴蝶监测数据集的分析为气候变化的生物影响提供了一些世界上最好的证据，包括主要的物候和分布变化、进化反应和极端事件的影响。人口趋势主要在国家范围内进行评估。该项目将对空间尺度(如跨区域、特定生境或个别地点)进行更详细的分析，以确定蝴蝶种群对主要变化驱动因素的反应。除了提供高影响力的科学见解外，这将支持更有效的保护，从当地的土地管理到跨区域的战略规划，包括制定新的生物多样性指标和站点级别的警报。国家范围的蝴蝶监测将通过完善受威胁物种的调查指南、改善蝴蝶寿命的知识和进一步评估物种受威胁状态的方法来加强。该项目将涉及新的统计模型开发和高分辨率土地覆盖数据的纳入。学生将组合多个复杂的生态数据集，并将产生新的人口指标，考虑到天气等外部因素的影响。

Three-quarters of UK butterfly species have declined over the past four decades. Butterflies respond quickly to habitat and climatic change, hence their population status is a valuable biodiversity indicator. Analysis of long-term butterfly monitoring datasets has provided some ofthe world's best evidence of the biological impacts of climate change, including major phenological and distribution shifts, evolutionary responses and the impacts of extreme events.Population trends are primarily assessed at national scales. This project will undertake more detailed analysis across spatial scales (e.g across regions, specific habitats or individual sites) to identify butterfly population responses to major drivers of change. As well as delivering high impact scientific insight, this will underpin more effective conservation, from local land management to strategic planning across regions, including the production of new biodiversity indicators and site level alerts.National-scale butterfly monitoring will be enhanced by refining survey guidance for threatened species, improving knowledge of butterfly lifespans and furthering methods for assessing species threatened status.The project will involve new statistical model developments and incorporation of high-resolution land-cover data. The student will combine multiple complex ecological datasets and will produce new population metrics, accounting for the influence of external factors such as weather.