Integrating and predicting responses of natural systems to disturbances

整合和预测自然系统对干扰的响应

• 批准号: NE/X013766/1
• 负责人: Roberto Salguero-Gomez
• 金额: $ 103.8万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FX013766%2F1
• 关键词: Integrating; predicting; responses; natural; systems

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.

确定机制，提供生态系统的能力，抵抗和恢复干扰，或过渡到替代状态，是量化和项目的生物多样性趋势的基础。弹性，一个系统对干扰的反应能力，自20世纪70年代以来吸引了生态学家的注意。然而，我们仍然不明白弹性是如何出现的，如何跨越生物组织的各个层次，也不知道它如何塑造它们的结构和动态。这种知识差距与国际政策不一致（例如，联合国可持续发展目标）认为保持生态系统的恢复力是可持续发展的关键。在这个项目中，我们将：目标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力，并开发新的理论来衡量个体，种群和社区对干扰的反应，目标2。揭示生物和非生物因素，以及它们的时间尺度，赋予全球数千个分类群，生活史策略和功能组的弹性，和目标3。将目标1和2的新发展应用于实验测试理论群落预测，该预测基于草原实验干扰的新全球网络中的个体和种群水平对干扰的反应。通过这个雄心勃勃的研究计划，新的方法，指标和知识将出现，以确定最具/最不具弹性的物种，功能群和世界各地对不同干扰制度的地区。在结构化人口统计学，社区矩阵理论，伪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，大型数据集，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，从而推动我们在这些关键领域的理解。