Integrating and predicting responses of natural systems to disturbances

确定为生态系统提供抵抗干扰和从干扰中恢复或向替代状态过渡的能力的机制，是量化和预测生物多样性趋势的基础。自20世纪70年代以来，一个系统对干扰作出反应的能力——恢复力就引起了生态学家的注意。然而，我们仍然不了解弹性是如何出现的，在生物组织的各个层面上是如何扩展的，也不了解它是如何塑造它们的结构和动态的。这种知识差距与国际政策（例如联合国可持续发展目标）不一致，这些政策认为保持生态系统的复原力是可持续发展的关键。在这个项目中，我们将：对象1。开发一个新的框架来量化和预测自然种群对现实干扰制度的恢复能力，并开发新的理论来衡量个体，种群和社区对干扰的反应，Obj 2。揭示生物和非生物因素及其时间尺度，这些因素赋予了全球数千个分类群、生活史策略和功能群体的恢复力，以及[j]。应用obs 1和obs 2的新发展，在一个新的全球草地实验扰动网络中，实验测试基于个体和种群水平对扰动响应的理论群落预测。通过这一雄心勃勃的研究计划，将出现新的方法、指标和知识，以确定世界上对不同干扰制度适应性最强/最弱的物种、功能群体和地区。在结构化人口学、群落矩阵理论、伪光谱理论和共存理论的基础上，我们将把这个框架应用于模拟、大数据集、长期记录和实地实验，以确定赋予生态系统弹性的机制。因此，该项目解决了生物学中的基本问题，并将有助于为实现关键的联合国可持续发展目标提供最佳实践，从而推动我们对这些关键领域的理解。

Identifying the mechanisms that provide ecological systems with the ability to resist and recover from disturbances, or transition to alternative states, is fundamental to quantify and project biodiversity trends. Resilience, a system's ability to respond to disturbances, has attracted the attention of ecologists since the 1970s. Yet, we still do not understand how resilience emerges, scales across levels of biological organisation, nor how it shapes their structure and dynamics. This knowledge gap is at odds with international policies (e.g., UN Sustainable Development Goals) that deem preserving the resilience of ecological systems key for sustainable development. In this project, we will:Obj 1. Develop a novel framework to quantify and predict the resilience of natural populations to realistic disturbance regimes and develop new theory to scale responses to disturbances across individuals, populations and communities,Obj 2. Reveal the biotic and abiotic factors, and their temporal scales, that confer resilience across thousands of taxa, life history strategies, and functional groups worldwide, andObj 3. Apply the novel developments from Objs 1 & 2 to experimentally test theoretical community predictions based on individual and population-level responses to disturbances in a new global network of experimental disturbances in grasslands.Through this ambitious research programme, novel methods, metrics, and knowledge will emerge to identify the most/least resilient species, functional groups, and regions of the world to different disturbance regimes. Grounded in structured demography, community matrix theory, pseudospectral theory, and coexistence theory, we will apply the framework to simulations, large datasets, long-term records, and field experiments to identify the mechanisms that confer resilience to ecological systems. As such, this project addresses fundamental questions in Biology and will help inform best practices to achieve key UN Sustainable Development Goals, thus Pushing the Frontiers of our understanding in these key areas.