RCN: DRAGNet - Disturbance and Recovery Across Grasslands

RCN：DRAGNet - 草原的干扰与恢复

• 批准号: 2311608
• 负责人: Elizabeth Borer
• 金额: $ 69.96万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311608&HistoricalAwards=false
• 关键词: RCN; DRAGNet; Disturbance; Recovery; Across

Physical disturbances (like plowing or animal wallowing) and increased supply of nutrients (like nitrogen and phosphorus) are changing Earth's terrestrial environments. However, predicting how plants and soils will respond remains uncertain. The project, DRAGNet (Disturbance and Recovery Across Grasslands Network), aims to address this by coalescing over 120 scientists from 93 grassland sites across Asia, Africa, Australia, Europe, North America, and South America. All scientists will conduct identical soil disturbance and nutrient addition experiments to understand how and where grassland communities respond to repeated disturbances and increased nutrients, how grasslands will recover from disturbance, and why similar places exhibit different responses to these changes. DRAGNet requires relatively low investment of time and money from individual researchers, enabling contributions from ecologists globally. Beyond scientific discoveries, the project aims to foster a diverse and inclusive research community, offering networking and collaboration opportunities, particularly for early-career researchers and scientists from developing countries. The findings from DRAGNet will be shared through publications, educational materials, and public talks. Coordination of this collaborative, global research network will provide deeper understanding of how ecosystems respond to disturbances and changes caused by human activities across the globe to better protect and preserve, both, wild and human-occupied environments.As a research coordination network, DRAGNet will allow comparisons of community responses in different grassland environments by coordinating identically replicated, factorial experiments manipulating soil disturbance and elemental nutrient supply at sites around the world. The data on plant and soil responses, collected following identical methods, will support tests of hypotheses about vegetation and biogeochemical resistance, the tendency to remain unchanged when disturbed, and recovery, the speed of return to a pre-disturbance state. By coordinating replicated experiments across site conditions, DRAGNet data will also uniquely clarify the context-dependence of post-disturbance responses on site history and conditions. In addition to testing hypotheses arising from ecological theory, project data will support development of a framework for understanding herbaceous system responses to these environmental changes by comparing recovery trajectories among diverse site conditions. The network will have four in-person and four virtual meetings to bring contributors together to analyze data, test hypotheses, and advance theoretical frameworks. In concert with scientific advances, the DRAGNet collaboration, especially the meetings, will serve to reduce isolation and increase inclusion, diversity, and scientific capacity, both, in the US and abroad. DRAGNet will advance research and facilitate collaboration and knowledge-sharing in the global scientific community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

物理干扰（如耕作或动物打滚）和营养物质（如氮和磷）供应的增加正在改变地球的陆地环境。然而，预测植物和土壤将如何反应仍然不确定。该项目名为DRAGNet（草地干扰与恢复网络），旨在通过联合来自亚洲、非洲、澳大利亚、欧洲、北美和南美93个草原地点的120多名科学家来解决这一问题。所有科学家将进行相同的土壤干扰和营养添加实验，以了解草原群落如何以及在何处对重复干扰和营养增加做出反应，草原如何从干扰中恢复，以及为什么相似的地方对这些变化表现出不同的反应。DRAGNet需要个人研究人员投入相对较少的时间和金钱，使全球生态学家能够做出贡献。除科学发现外，该项目还旨在培养一个多样化和包容性的研究社区，提供网络和合作机会，特别是为来自发展中国家的早期职业研究人员和科学家提供机会。DRAGNet的调查结果将通过出版物、教育材料和公开讲座分享。协调这一合作性全球研究网络将使人们更深入地了解生态系统如何应对地球仪上人类活动造成的干扰和变化，以更好地保护和维护野生和人类居住的环境。因子实验操纵土壤扰动和元素养分供应在世界各地的网站。按照相同的方法收集的植物和土壤反应数据将支持关于植被和土壤地球化学抗性的假设检验，即受干扰时保持不变的趋势，以及恢复，即恢复到干扰前状态的速度。通过协调不同场地条件下的重复实验，DRAGNet数据还将独特地澄清干扰后响应对场地历史和条件的依赖性。除了测试从生态理论产生的假设，项目数据将支持一个框架的发展，了解草本植物系统对这些环境变化的反应，比较不同的网站条件之间的恢复轨迹。该网络将有四个面对面的会议和四个虚拟会议，将贡献者聚集在一起分析数据，测试假设和推进理论框架。与科学进步相一致，DRAGNet合作，特别是会议，将有助于减少孤立，增加包容性，多样性和科学能力，无论是在美国还是国外。DRAGNet将推动研究，促进全球科学界的合作和知识共享。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。