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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：时间的不确定性是否导致游牧？所有动物的运动都受到它们对食物等资源的需求的影响。动物迁移的地点和速度通常取决于在哪里可以找到最好的植被资源，以及这种食物每年的可预测性。一些有蹄类动物在可预测的环境中季节性迁移，驯鹿和角马就是这样的例子。其他一些物种--例如瞪羚--似乎会进行大规模、长距离的运动，这似乎是不可预测的。当资源的可用性和位置因季节和年份而变化很大时，这种“游牧”可能会发生。为了理解这些季节性和年度运动策略，研究人员将结合联合收割机：1）理论计算机模型，2）植被的卫星图像，3）蒙古瞪羚个体（新的实地研究）和阿拉斯加驯鹿（历史数据）的详细运动数据。通过了解长距离的动物运动，我们将更好地了解环境变化如何影响动物行为。保护这些物种及其栖息地取决于了解它们的大规模移动模式和生态。我们的研究将有助于确定动物“阅读”环境的机制，以了解何时何地在复杂的景观中移动。