BioDT - Biodiversity Digital Twin for Advanced Modelling, Simulation and Prediction Capabilities
BioDT - Biodiversity Digital Twin for Advanced Modelling, Simulation and Prediction Capabilities
批准号:
10039292
负责人:
金额:
$46.76万
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
随着地球生物多样性的日益减少,了解气候、人类、污染和其他因素对生物多样性的影响是至关重要的。这一需求是迫切的,因为生物多样性的丧失直接影响到我们作为人类的生存能力。例如,这种损失降低了生态群落获取基本资源、产生生物量、分解有机物和循环养分的效率。此外,越来越多的证据表明,缺乏与自然生物多样性的接触会通过对微生物组和免疫系统的负面影响影响人类健康。微生物群和免疫系统。了解形成生物多样性的力量是合理管理自然资源的基础,也是欧盟《2030年生物多样性战略》的关键推动因素,该战略旨在到2030年使欧洲的生物多样性走上恢复之路,造福人类、气候和地球。特别是,我们需要能够更好地预测全球生物多样性动态:物种如何与环境以及彼此之间相互作用。我们的目标是通过开发提供先进建模、模拟和预测能力的数字孪生,推动生物多样性动态预测理解的当前边界。通过以新的方式利用相关研究基础设施中现有的技术和数据,BioDT项目将能够更准确地模拟物种与其环境之间的相互作用。研究基础设施的科学家将能够使用BioDT来1)更好地观察生物多样性的变化,2)将这些变化与可能的原因联系起来,以及3)根据气候或人类干预对这些原因的影响更好地预测变化的影响。我们的联盟汇集了生物多样性,高性能计算,人工智能和FAIR数据方面的专家团队,以实现第一个生物多样性数字孪生原型。
英文摘要
With our planet facing an increasing reduction in biodiversity, it is of the utmost importance to understand the way climate, humans, pollution and other factors affect biodiversity. This need is urgent since biodiversity loss directly impacts our ability as humans to live. For example, this loss reduces the efficiency with which ecological communities capture essential resources, produce biomass, decompose organic matter and recycle nutrients. Furthermore, there is increasing evidence that a lack of contact with natural biodiversity impacts human health through negative effects in the microbiome and immune system. microbiome and immune system. Understanding the forces shaping biodiversity is the basis for any rational management of natural resources and will be a key enabler of the EU Biodiversity Strategy 2030 which aims to put biodiversity in Europe on the path to recovery by 2030 for the benefit of people, climate and the planet. In particular, we need to be able to better predict global biodiversity dynamics: how species interact with their environment and with each other. Our goal is to push the current boundaries of predictive understanding of biodiversity dynamics by developing a Digital Twin providing advanced modelling, simulation and prediction capabilities. By exploiting in new ways existing technologies and data available across relevant research infrastructures, the BioDT project will be able to more accurately model interaction between species and their environment. Scientists at Research Infrastructures will be able to use the BioDT to 1) better observe changes in biodiversity, 2) relate these changes to possible causes, and 3) better predict effects of changes based on influences on these causes by either climate or human intervention. Our consortium brings together a dynamic team of experts in biodiversity, high performance computing, artificial intelligence and FAIR data to realise the first biodiversity Digital Twin prototype.
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