The Effect of Anthropogenic Disturbance on the Dynamics of Sin Nombre

人为干扰对 Sin Nombre 动态的影响

• 批准号: 0326999
• 负责人: Maria Denise Dearing
• 金额: $ 182.38万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0326999&HistoricalAwards=false
• 关键词: Effect; Anthropogenic; Disturbance; Dynamics; Sin

Sin Nombre hantavirus (SN) is a recently discovered virus carried by deermice that causes disease with high mortality in humans. Several recent studies have proposed that human disturbance of habitat significantly affects the number of deermice infected with SN. Given unprecedented rates of disturbance and limited understanding of the mechanisms governing variation in SN infection, a thorough study of how disturbance affects SN dynamics is warranted. The central focus of the proposed study is to determine how human disturbance affects SN prevalence in deermice and other reservoirs. To address this issue, a multifaceted research program is proposed that includes empirical and theoretical work. The field data will be used to determine the underlying mechanisms responsible for differences in prevalence. These ground-based data will be used to generate predictive mathematical models of prevalence using aerial and satellite images.The broader impacts of this study include education, interdisciplinary research and national security. Several undergraduate and graduate students will be trained as part of this research. The project unites scientists from diverse fields (geography, mathematics, ecology, virology). Lastly, the research will yield critical information on the biology of Sin Nombre virus, which is listed as a biological agent of concern for national security.

Sin Nombre汉坦病毒（SN）是最近发现的一种由鹿鼠携带的病毒，可引起人类高死亡率的疾病。 最近的几项研究表明，人类对栖息地的干扰显著影响了感染SN的鹿鼠数量。 鉴于前所未有的干扰率和有限的了解，在SN感染的变化机制，干扰如何影响SN动态的深入研究是必要的。 拟议研究的中心重点是确定人类干扰如何影响鹿鼠和其他水库的SN患病率。为了解决这个问题，提出了一个多方面的研究计划，包括经验和理论工作。 实地数据将用于确定造成流行率差异的潜在机制。 这些地面数据将用于利用航空和卫星图像生成流行率预测数学模型，这项研究的更广泛影响包括教育、跨学科研究和国家安全。一些本科生和研究生将接受培训，作为这项研究的一部分。 该项目联合了来自不同领域（地理学，数学，生态学，病毒学）的科学家。 最后，这项研究将产生关于Sin Nombre病毒生物学的重要信息，该病毒被列为国家安全关注的生物制剂。