U.S.-Tanzania Planning Visit: Investigating Patterns of Self-organization in Large Vertebrates Using Very High-resolution Satellite Imagery

美国-坦桑尼亚计划访问：利用超高分辨率卫星图像研究大型脊椎动物的自组织模式

• 批准号: 1427740
• 负责人: Douglas McCauley
• 金额: $ 7.46万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1427740&HistoricalAwards=false
• 关键词: U.S.; Tanzania; Planning; Visit; Investigating

This CNIC project will allow the PI, Douglas McCauley of the University of California at Santa Barbara (UCSB) to develop a research area that is new to him via a collaborative research effort with researchers at Sokoine University of Agriculture (SUA) in Morogoro, Tanzania and a complementary research team in a different department at UCSB. The goal of the project is to evaluate and adapt new, very high-resolution satellite data and computational analysis tools to directly study self-organization of large vertebrates. The key intellectual merit of this project is to perform proof-of-concept demonstrating that high-resolution satellite data can be used to understand the scale, scope and parameters of self-organization geometries in large vertebrates. This effort could have a transformative impact on the scale and scope at which self-organization in vertebrates can be evaluated. Self-organization geometries in animals, that is the collective behaviors that shape the geometry of animal aggregations, have thus far focused primarily on small vertebrates (e.g. minnows) and satellite data has not been utilized as a data source. By exploring a new and significantly different set of animals this project may significantly contribute to the understanding of group behavior and pattern formation in nature. The goal of this CNIC proposal is to identify the necessary sub-meter panchromatic and multispectral satellite data for a small pilot study in the Greater Serengeti Ecosystem, ground truth the satellite data and validate the computer-assisted analysis tools that will be applied, in this pilot effort, to evaluating self-organization geometries of migrating wildebeest herds. These techniques may allow study of how group architecture and migratory behaviors have been altered by environmental change. More significantly, by comparing conclusions drawn from the study of self-organization in large groups of large vertebrates to those generated in groups of smallbodied aggregating organisms, it will be possible to better understand the general principles that control animate self-organization. The research is also likely to result in tools and information that can assist the management of large vertebrates in ecosystems around the world that are undergoing significant change.

这个CNIC项目将使加州大学圣巴巴拉分校(UCSB)的PI道格拉斯·麦考利(Douglas McCauley)通过与坦桑尼亚莫罗戈罗索科内农业大学(SUA)的研究人员和UCSB不同系的补充研究团队的合作研究，开发一个对他来说是新的研究领域。该项目的目标是评估和调整新的、非常高分辨率的卫星数据和计算分析工具，以直接研究大型脊椎动物的自我组织。这个项目的关键智力优势是进行概念验证，证明高分辨率卫星数据可以用来理解大型脊椎动物自组织几何的规模、范围和参数。这一努力可能会对评估脊椎动物自组织的规模和范围产生革命性的影响。到目前为止，动物的自组织几何，即塑造动物聚集几何的集体行为，主要集中在小型脊椎动物(如小鱼)上，卫星数据尚未被用作数据源。通过探索一组新的和显着不同的动物，这个项目可能会对理解自然界中的群体行为和模式形成做出重大贡献。CNIC建议的目标是为大塞伦盖蒂生态系统的一项小型试点研究确定必要的亚米级全色和多光谱卫星数据，核实卫星数据的真实性，并验证计算机辅助分析工具，这些工具将在这项试点工作中用于评估迁徙的角马种群的自组织几何形状。这些技术可能有助于研究群体结构和迁徙行为如何因环境变化而改变。更重要的是，通过将大型脊椎动物大群体的自组织研究得出的结论与小型聚集有机体群体产生的结论进行比较，将有可能更好地理解控制生物自组织的一般原理。这项研究还可能产生工具和信息，帮助管理世界各地正在经历重大变化的生态系统中的大型脊椎动物。