DISSERTATION RESEARCH: Ungulate Movement Strategies and Resource Predictability in Grassland Ecosystems

论文研究：草原生态系统中有蹄类动物的运动策略和资源可预测性

• 批准号: 0608224
• 负责人: William Fagan
• 金额: $ 1.18万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0608224&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; Ungulate; Movement; Strategies

This research seeks to better understand the underlying behavioral mechanisms associated with the movement strategies of ungulates as they travel through different landscapes. Animal movements are usually motivated by a need for resources and among ungulates, some species (e.g., white-tailed deer) have generally abundant and well-dispersed resources and are considered range-residents, whereas other species (e.g., caribou, wildebeest), whose resources are predictably distributed in different parts of their range in different seasons, are migratory. However, large-scale, long-range movements that occur when resource distributions are fundamentally unpredictable in both time and space have so far received little attention. These movements could be called nomadism and one striking example can be observed in Mongolian gazelles, which are the most important wild ungulate in one of the last intact temperate grassland ecosystem on the planet. We will develop computer models that simulate and link behavioral movement mechanisms which can be either based on memory, perceptual cues or triggered by environmental factors. It explores their efficiency under different scenarios of resource distributions across time and space. Finally it tries to integrate empirical data on resource distributions as well as movements of moving animals, such as satellite data on primary productivity and satellite tracking data of Mongolian gazelles. New insights about the driving forces of ungulate movements will support conservation efforts for nomadic and migratory species in general and Mongolian gazelles specifically, which are constantly moving and difficult to manage with traditional static protected areas.

本研究旨在更好地理解有蹄类动物穿越不同景观时与运动策略相关的潜在行为机制。动物运动通常是由对资源的需求驱动的，在有蹄类动物中，一些物种（如白尾鹿）通常拥有丰富而分散的资源，被认为是范围居民，而其他物种（如北美驯鹿、角马），其资源在不同季节可预测地分布在其范围的不同部分，是迁徙性的。然而，当资源分配在时间和空间上根本不可预测时发生的大规模、远距离移动迄今很少受到注意。这些运动可以被称为游牧，蒙古瞪羚就是一个显著的例子，它们是地球上最后一个完整的温带草原生态系统中最重要的野生有蹄类动物。我们将开发计算机模型来模拟和连接行为运动机制，这些机制可以基于记忆，感知线索或由环境因素触发。探讨了不同时空资源分配情景下的效率。最后，尝试整合资源分布和动物运动的经验数据，如初级生产力的卫星数据和蒙古瞪羚的卫星跟踪数据。关于有蹄类动物运动驱动力的新见解将支持对游牧和迁徙物种的保护工作，特别是对蒙古瞪羚的保护，这些物种不断移动，难以用传统的静态保护区进行管理。