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| COLLABORATIVE RESEARCH: Defining Stream Biomes to Better Understand and Forecast Stream Ecosystem Change | |
| 项目编号 | 1442522 |
| Nancy Grimm | |
| 项目主持机构 | Arizona State University |
| 开始日期 | 2015-09-15 |
| 结束日期 | 08/31/2022 |
| 英文摘要 | Biologists have used a well accepted classification system to identify regional areas by the major or predominant vegetation biomes. This largely land-based classification system has been very useful in conducting research and understanding the environmental, geological, and biological features of those regions. These factors influence how ecological systems within the biome are structured and how they function. The classification scheme provides a framework for site- specific research to be understood in a larger regional context and scale the results to the larger region. A weakness or missing part of this framework is streams and rivers. Most maps or lists of biomes of the world would suggest that flowing waters are so similar to one another that all streams can be lumped into a single category. They are generally lumped together regardless of the regional geology, watershed vegetation, or climatic factors. This research will develop a biome classification system for streams to better understand how streams function and provide an ability to predict how streams will change from human and environmental factors. This continental scale project will address the deceptively simple question: is there such a thing as a stream biome? From an ecosystem perspective we now know that inland waters play critical roles in both global carbon (C) and nitrogen (N) cycling. The physical diversity of lotic waters as well as their tendency is more temporally dynamic than terrestrial systems. Ultimately the phenology of stream ecosystem energetics will be a function of energy supply (light and fixed terrestrial carbon) and fixed carbon removal (via hydrologic disturbance). Watershed structure determines the route and rate at which water enters stream channels while watershed vegetation determines the magnitude and timing of fixed carbon inputs and the degree and temporal patterning of light availability. This research effort will increase the measurements of annual metabolism by nearly two orders of magnitude. At the present time there exist only two streams for which annual metabolic rates have been calculated using continuous dissolved oxygen measurements. By the conclusion of this project 55 years of high quality metabolism data will have been generated for a total of 35 streams, and the project PIs will have acquired (via leveraged funds and collaborations) metabolism data for at least 196 additional streams. Metabolism metrics from all of these streams will be used to build the first hierarchical classification of stream ecosystems based on their seasonal and annual patterns of primary productivity and ecosystem respiration. Stream biome delineation will facilitate estimation of stream metabolic rates at timescales of days to years for spatial scales from reaches to river networks. Simulation models, developed from first principles and refined with empirical data specific to each biome, will forecast changes in metabolic rates in response to likely climate and land use change scenarios. The data management plan has been designed in collaboration with informatics staff of the USGS Center for Integrated Data Analytics and USGS has agreed to host and help develop a public data repository, modeling, and data visualization platform specifically designed to collate long-term or high-resolution metabolism and dissolved oxygen datasets for streams. By building, refining and activating a community data platform this research program will change the way individual streams are studied and will facilitate and encourage near instantaneous cross-site synthesis. In addition to capacity building, this project will directly support seven graduate students and 7 postdoctoral associates over the funding period. |
| 资助机构 | US-NSF |
| 项目经费 | $547,569.00 |
| 项目类型 | Standard 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/212760 |
| 推荐引用方式 GB/T 7714 | Nancy Grimm.COLLABORATIVE RESEARCH: Defining Stream Biomes to Better Understand and Forecast Stream Ecosystem Change.2015. |
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