Collaborative Research: ITR/AP (DEB) Stochastic Synthesis: Simulating the Environmental Transformations of Natural Organic Matter

合作研究：ITR/AP (DEB) 随机合成：模拟天然有机物的环境转变

• 批准号: 0113570
• 负责人: Stephen Cabaniss
• 金额: $ 29.86万
• 依托单位: Kent State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0113570&HistoricalAwards=false
• 关键词: Collaborative; Research; ITR; AP; DEB

The waters and soils of our environment contain naturally-occurring organic matter (NOM), which helps to regulate soil fertility, pollutant toxicity, ecosystem behavior and carbon cycling. These in turn affect agricultural production, public and ecosystem health, and global climate change. However, the processes which produce NOM from plant and animal matter are poorly understood, due to the complex nature of NOM and the multitude of possible reactions in the environment. This project will combine the efforts of ecologists, geochemists and computer scientists in an attempt to model this complex system using a novel stochastic approach. In this approach, millions of individual molecules are simulated and reacted together 'in silico' to provide a computer model of the complex natural processes. The model will be developed and tested via an internet collaboration, and ultimately will be accessible to agricultural, environmental and earth scientists via a simple web browser interface.

我们环境中的沃茨和土壤含有天然存在的有机物质（NOM），有助于调节土壤肥力、污染物毒性、生态系统行为和碳循环。 这些反过来又影响到农业生产、公共和生态系统健康以及全球气候变化。 然而，由于NOM的复杂性质和环境中可能的多种反应，从植物和动物物质产生NOM的过程知之甚少。 这个项目将联合收割机的努力，生态学家，地球化学家和计算机科学家，试图模拟这个复杂的系统使用一种新的随机方法。 在这种方法中，数以百万计的单个分子被模拟并“在计算机上”一起反应，以提供复杂自然过程的计算机模型。 该模型将通过互联网合作进行开发和测试，最终将通过简单的网络浏览器界面提供给农业，环境和地球科学家。