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| Collaborative Research: Network Cluster: Using Big Data approaches to assess ecohydrological resilience across scales | |
| 项目编号 | 2012188 |
| Adrian Harpold | |
| 项目主持机构 | Board of Regents, NSHE, obo University of Nevada, Reno |
| 开始日期 | 2020-09-01 |
| 结束日期 | 08/31/2025 |
| 英文摘要 | The part of the Earth surface that sustains life (the Critical Zone) consists of bedrock, soil, water, air, and living things that have been interacting for billions of years. The Critical Zone can absorb many disturbances while still supporting life on Earth, but the age of humans or the “Anthropocene” has put unprecedented pressure on the Critical Zone. When long-term disturbances like climate change are combined with short-term disturbances like fires or flooding, ecosystems can be pushed past a breaking point where important ecosystem services shut down. This project seeks to understand and predict Critical Zone resilience in the face of multiple natural and human disturbances. The research will combine river flow and chemistry data from throughout the U.S. to shed light on how quickly ecosystems recover from local disturbances and to what degree long-term change is altering the structure of the Critical Zone. The team of researchers will combine ecological approaches with data science methods to analyze large quantities of information from thousands of locations. Existing data from public and private organizations across the U.S. will be compiled into a publicly available data base to compare ecosystem recovery times and trajectories. The general patterns observed in the “big data” analysis will be tested by in-depth field studies at four sites experiencing multiple disturbances such as wildfire, acidification, and extreme storms. This project will help Earth science researchers and educators across the U.S. develop a deeper understanding of how the Earth system maintains itself and how humans can avoid eroding the ecosystem services that sustain us. To achieve this goal, all data and approaches will be shared publicly and the research team will lead an innovative outreach and education program. This comprehensive program will educate 7-12 grade teachers to bring cutting-edge ecology and data science to schools across America. To enhance diversity in Earth science and data science, a field camp will be co-designed and implemented in collaboration with historically black colleges and universities. While observatory-based Critical Zone research produces important findings on catchment-scale processes, the global scale of disturbance in the Anthropocene transcends the bounds of a single site or funding cycle, posing a challenge for traditional investigative approaches. This spatial and temporal mismatch significantly limits the predictive power of individual site studies in the context of regional- to continental-scale environmental change. To advance network-scale syntheses and integrate across scales, this project will apply an iterative “pattern to process” and “process to pattern” approach to investigate how Critical Zone structure controls water, carbon, nutrients, and response to overlapping disturbances in the context of multi-dimensional resilience. In this context, the overarching hypothesis is that Critical Zone structure (i.e. configuration of biological, chemical, and physical characteristics) controls the timing, direction, and intensity of linkages among multiple responses and that these linkages regulate ecosystem resilience and resistance to climate and land cover disturbance. To test this overarching hypothesis, (1) existing ecohydrological data will be compiled from across the continental U.S. into a multi-dimensional Critical Zone database, (2) advanced statistical analysis will be performed using complex-systems tools on “big data” to identify state changes in ecological function and ecosystem services, (3) process-hypotheses will be refined based on these data-driven approaches, and (4) in-depth process investigations will be performed at four high-vulnerability focal sites in the northeast and southwest. The database and complex-systems approaches will be shared to empower the Critical Zone community to transition into a phase of data-driven hypothesis generation and cross-site research. To broaden the participation of underrepresented groups in Critical Zone and data science the project will educate and empower a diverse new generation of STEM thinkers from middle and high school to the graduate college level. A comprehensive grade 7-12 education program will reach hundreds of students from high-need Vermont schools (historically marginalized economic, racial or disability groupings) by “educating the educators” in Critical Zone and data science. Furthermore, in collaboration with HBCUs, outdoor education on Critical Zone and data science will be designed and implemented for a diverse group of undergraduate students. This project is jointly funded by the Critical Zone Collaborative Network Program, the Hydrologic Sciences Program in the NSF Division of Earth Sciences, and the Established Program to Stimulate Competitive Research (EPSCoR). 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. |
| 资助机构 | US-NSF |
| 项目经费 | $232,486.00 |
| 项目类型 | Continuing Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/211527 |
| 推荐引用方式 GB/T 7714 | Adrian Harpold.Collaborative Research: Network Cluster: Using Big Data approaches to assess ecohydrological resilience across scales.2020. |
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