Doctoral Dissertation Research: Detecting Anthropogenic Forest Disturbances and Understory Density for the Study of Hantavirus in Paraguay

博士论文研究：巴拉圭汉坦病毒研究中检测人为森林干扰和林下密度

• 批准号: 0826297
• 负责人: Douglas Goodin
• 金额: $ 1.16万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0826297&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Detecting; Anthropogenic

Landscape epidemiology is the study of the effect that landscape has on disease occurrence, transmission, and persistence. Hence, the quality of landscape epidemiology research frequently depends on the accuracy and reliability of land cover information. For zoonotic diseases, this means a needed focus on the aspects of the landscape that form the habitat of the host. Hantavirus, a zoonotic virus hosted by rodents of the murine family, is one example of an etiological organism whose dynamics are known to be related to landscape factors. With some hantavirus reservoir species, forest disturbances are important factors in disease transmission. Frequently, land cover maps developed using existing remote sensing techniques consider only the binary distinction between forested and deforested cover. Based on ongoing research, it appears that forests with intermediate disturbances are in fact one of the key habitat types associated with high hantavirus prevalence in rodent communities. Improved methods are therefore needed to differentiate levels of disturbance remotely, in order to map areas at risk for the occurrence and spread of hantavirus. This research will address the question: How can we improve landcover mapping of different types of forest and forest disturbances to facilitate landscape epidemiology studies of hantavirus in the Paraguayan Atlantic Forest? Selected plots representing a gradient of forest disturbance within the Mbaracayu Biosphere in Paraguay will be field surveyed to determine understory and canopy structure and composition. Each sample plot will have a nested sub-plot design, with 100x100m plots to measure trees, a smaller plot in the center to measure shrub density, and nine subplots to measure ground cover. These field data will be used to relate the canopy and understory structures, as determined in the field plots, to remotely sensed landscape metrics derived from object-oriented image analysis at a variety of spatial scales. It is expected that this study will lead to improved estimation of forest disturbances and differences in understory density using remotely sensed imagery, with implications for studying diseases. The research in this project will more closely tie the use of remotely sensed data to landscape epidemiology applications. The developed techniques will be applicable to analyzing remotely sensed data in a way that is more useful to studying the ecology of hantavirus, as well as a range of other zoonotic diseases. Additionally, the techniques will be generally applicable to landscape ecology and biogeography studies in forested landscapes. Currently, detecting deforestation with remotely sensed data often is treated as a binary task, forested and deforested, but in reality, there are many levels of forest disturbance that can be important to various natural systems. This research will improve the ability to detect and map different levels and kinds of forest disturbance, enabling more detailed analysis of the ecological effect of those disturbances. Other potential benefits of this study include improved understanding of the Atlantic forest in Eastern Paraguay, a little known and endangered ecosystem and biodiversity hotspot. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.

景观流行病学是研究景观对疾病发生、传播和持续性的影响。因此，景观流行病学研究的质量往往取决于土地覆盖信息的准确性和可靠性。对于人畜共患病，这意味着需要关注构成宿主栖息地的景观方面。汉坦病毒是一种由鼠科啮齿动物宿主的人畜共患病毒，是已知其动态与景观因素有关的病原生物的一个例子。对于一些汉坦病毒的宿主物种，森林干扰是疾病传播的重要因素。利用现有遥感技术绘制的土地覆盖图往往只考虑森林覆盖和森林砍伐覆盖之间的二元区别。根据正在进行的研究，似乎中度干扰的森林实际上是与啮齿动物群落中汉坦病毒高流行率相关的关键栖息地类型之一。因此，需要改进方法，以远距离区分干扰程度，以便绘制汉坦病毒发生和传播风险地区的地图。这项研究将解决的问题：我们如何才能提高土地覆盖映射不同类型的森林和森林干扰，以促进汉坦病毒的景观流行病学研究，在大西洋森林？将对巴拉圭Mbaracayu生物圈内代表森林干扰梯度的选定地块进行实地调查，以确定林下和树冠结构和组成。每个样地将有一个嵌套的子区设计，100x100米的地块测量树木，一个较小的地块在中心测量灌木密度，和九个子区测量地面覆盖。这些实地数据将用于将实地图中确定的树冠和林下结构与从各种空间尺度上面向对象的图像分析得出的遥感景观指标联系起来。预计这项研究将导致使用遥感图像改进对森林干扰和林下植被密度差异的估计，并对疾病研究产生影响。本项目的研究将把遥感数据的使用与环境流行病学应用更密切地联系起来。所开发的技术将适用于分析遥感数据，对研究汉坦病毒生态学以及一系列其他人畜共患疾病更为有用。此外，该技术将普遍适用于景观生态学和森林景观地理学研究。目前，利用遥感数据检测森林砍伐情况往往被视为一项二元任务，即森林覆盖和森林砍伐，但实际上，森林干扰的程度有很多，对各种自然系统都很重要。这项研究将提高对不同程度和种类的森林干扰进行检测和绘图的能力，从而能够更详细地分析这些干扰的生态影响。这项研究的其他潜在好处包括提高对巴拉圭东部大西洋森林的了解，这是一个鲜为人知的濒危生态系统和生物多样性热点。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立的研究生涯。