Doctoral Dissertation Research: Spatial and Temporal Habitat Use of Elephants in the Serengeti Ecosystem: A Predictive Modeling Approach Using Multiscale Satellite Imagery

博士论文研究：塞伦盖蒂生态系统中大象的时空栖息地利用：利用多尺度卫星图像的预测建模方法

• 批准号: 0826042
• 负责人: Herman Shugart
• 金额: $ 1.2万
• 依托单位: University of Virginia Main Campus
• 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: 2008-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0826042&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Spatial; Temporal

The conservation of Africa's remaining elephant populations and their habitats has emerged as one of the continent's greatest wildlife management challenges. In savanna ecosystems in sub-Saharan African, elephants are one of the major sources of disturbance influencing vegetation dynamics and structure. In rural areas adjacent to protected areas, elephants are also major contributors to human-wildlife conflict. Both human-elephant conflict (HEC) and the impacts of elephants on woody vegetation have the potential to intensify as elephant populations recover after the intense poaching of the 1970s and 1980s, while former elephant range becomes increasingly restricted by human settlement. The 25,000 square kilometer Serengeti ecosystem in northern Tanzania and southern Kenya is one of the best studied savanna ecosystems in the world. However, very few studies on elephant population dynamics or ecology have been conducted in recent decades, which represents a significant knowledge gap given the importance of elephants in shaping this ecosystem, and the changes in climate, vegetation cover and human and elephant populations that have occurred during the past decades. This project will employ a combination of field measurements of vegetation structure, optical and radar remote sensing, and satellite tracking of elephants in the Serengeti ecosystem of Tanzania to map savanna structure at multiple spatial scales. These mapped variables will be used to predict elephant presence/absence (obtained from satellite telemetry) within quantitative distribution models, which will improve understanding of the following aspects of elephant ecology: 1) the habitat variables that influence elephant habitat selection within a savanna ecosystem, and the scales at which these operate; 2) the factors that predict elephant use of human-dominated landscapes, and thus HEC. Time-series radar and optical satellite images will be used to identify patterns of woody vegetation change in the study area. The observed trends in vegetation change will be evaluated against models of elephant habitat use, remote sensing derived fire histories, and climate data to better understand the role of elephants as agents of change in the Serengeti ecosystem.This study will use techniques novel to investigations of elephant habitat selection and their impacts on savanna woodland structure, making significant contributions both to the fields of savanna ecology and wildlife-habitat interactions. It will be one of the first studies to use remote sensing technology at landscape scales to address the role of elephants as ecosystem modifiers. The project will further contribute to a growing field of study focused around HEC, by providing a landscape-scale assessment of the factors contributing to elephant use of human-dominated areas, and will provide information essential to appropriate ecosystem management in one of Africa's best-known wildlife areas. Results of the study will enable protected area managers to incorporate information both on the impacts of a growing elephant population on savanna habitats, and on ecological correlates of HEC, into management and mitigation plans.This award is co-funded by NSF's Office of International Science and Engineering.

保护非洲剩余的大象种群及其栖息地已成为非洲大陆野生动物管理面临的最大挑战之一。 在撒哈拉以南非洲的稀树草原生态系统中，大象是影响植被动态和结构的主要干扰源之一。 在保护区附近的农村地区，大象也是人类与野生动物冲突的主要根源。人象冲突 (HEC) 和大象对木本植被的影响都有可能加剧，因为大象数量在 20 世纪 70 年代和 80 年代的大规模偷猎之后有所恢复，而以前的大象活动范围也越来越受到人类住区的限制。 坦桑尼亚北部和肯尼亚南部面积达 25,000 平方公里的塞伦盖蒂生态系统是世界上研究最深入的稀树草原生态系统之一。然而，近几十年来，对大象种群动态或生态学的研究很少，考虑到大象在塑造这一生态系统中的重要性，以及过去几十年来气候、植被覆盖以及人类和大象种群发生的变化，这代表了巨大的知识差距。 该项目将结合植被结构的实地测量、光学和雷达遥感以及坦桑尼亚塞伦盖蒂生态系统中大象的卫星跟踪，以绘制多个空间尺度的稀树草原结构图。这些映射的变量将用于预测定量分布模型中大象的存在/不存在（通过卫星遥测获得），这将增进对大象生态学以下方面的理解：1）影响稀树草原生态系统内大象栖息地选择的栖息地变量，以及这些变量运行的规模； 2) 预测大象使用人类主导的景观的因素，从而预测 HEC。时间序列雷达和光学卫星图像将用于识别研究区域木本植被变化的模式。 观察到的植被变化趋势将根据大象栖息地利用模型、遥感火灾历史和气候数据进行评估，以更好地了解大象作为塞伦盖蒂生态系统变化推动者的作用。这项研究将使用新颖的技术来调查大象栖息地选择及其对稀树草原林地结构的影响，为稀树草原生态和野生动物-栖息地相互作用领域做出重大贡献。这将是首批在景观尺度上使用遥感技术来解决大象作为生态系统调节者的作用的研究之一。该项目将通过对影响大象利用人类主导地区的因素进行景观尺度评估，进一步促进以 HEC 为重点的不断发展的研究领域，并将为非洲最著名的野生动物地区之一的适当生态系统管理提供必要的信息。 该研究的结果将使保护区管理人员能够将有关大象数量不断增长对稀树草原栖息地的影响以及 HEC 的生态相关性的信息纳入管理和缓解计划中。该奖项由美国国家科学基金会国际科学与工程办公室共同资助。