COLLABORATIVE RESEARCH: QEIB: Resource Predictability and Dispersal Strategies in Ungulates: Does Temporal Uncertainty Lead to Nomadism?

合作研究：QEIB：有蹄类动物的资源可预测性和扩散策略：时间不确定性会导致游牧吗？

基本信息

批准号：
0743557
负责人：
William Fagan
金额：
$ 14.72万
依托单位：
University of Maryland, College Park
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2008
资助国家：
美国
起止时间：
2008-06-15 至 2012-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0743557&HistoricalAwards=false
关键词：
COLLABORATIVE RESEARCH QEIB Resource Predictability

项目摘要

Resource Predictability and Movement Strategies in Ungulates:Does Temporal Uncertainty Lead to Nomadism? The movements of all animals are affected by their need for resources such as food. Where and how quickly animals move often depends on where the best vegetation resources can be found and how predictable this food is from year to year. Some ungulate species with predictable environments migrate seasonally; caribou and wildebeest are examples of this. A few other species - gazelles, for example - appear to make large-scale, long-range movements that are seemingly unpredictable. This 'nomadism' likely occurs when the availability and location of resources varies considerably by season and by year. To make sense of these seasonal and annual movement strategies, researchers will combine: 1) theoretical computer models, 2) landscape-scale satellite images of vegetation, and 3) detailed movement data from individual gazelles in Mongolia (new field studies) and caribou in Alaska (historical data). By understanding long-distance animal movements, we will be in a much better position to know how environmental variability affects animal behavior. The conservation of these species and their habitats depends on understanding their large-scale movement patterns and ecology. Our research will help identify the mechanisms by which animals 'read' their environment to know when and where to move over complex landscapes.

有蹄类动物的资源可预测性和运动策略：时间不确定性会导致游牧吗？所有动物的活动都受到其对食物等资源的需求的影响。动物迁徙的地点和速度通常取决于哪里可以找到最好的植被资源，以及这些食物每年的可预测性。一些环境可预测的有蹄类动物会季节性迁徙；驯鹿和角马就是这样的例子。其他一些物种（例如瞪羚）似乎会进行看似不可预测的大规模、长距离运动。当资源的可用性和位置随季节和年份变化很大时，可能会发生这种“游牧”。为了理解这些季节性和年度运动策略，研究人员将结合：1）理论计算机模型，2）植被的景观尺度卫星图像，以及3）来自蒙古个体瞪羚（新实地研究）和北美驯鹿的详细运动数据。阿拉斯加（历史数据）。通过了解动物的长距离运动，我们将能够更好地了解环境变化如何影响动物行为。这些物种及其栖息地的保护取决于对它们大规模运动模式和生态的了解。我们的研究将有助于确定动物“解读”其环境的机制，以了解何时何地在复杂的景观中移动。