4.5 Article

Predation risk, gender and the group size effect: does elk vigilance depend upon the behaviour of conspecifics?

期刊

ANIMAL BEHAVIOUR
卷 66, 期 -, 页码 389-398

出版社

ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
DOI: 10.1006/anbe.2003.2217

关键词

-

向作者/读者索取更多资源

Many animals benefit from the presence of conspecifics by reducing their rate of scanning for predators while increasing their time spent foraging. This group size effect could arise from a decreased perception of individual risk (dilution hypothesis) and/or an increased ability to detect predators (detection hypothesis). We compared individual and group vigilance of Rocky Mountain elk, Cervus elaphus, in three regions of Yellowstone National Park, Wyoming, U.S.A. that varied in their encounter frequency with coyote, Canis latrans, grizzly bear, Ursus arctos, and grey wolf, Canis lupus, predators. Adult females without calves increased scanning and decreased foraging with high encounter risk and small herd size. Adult females with calves increased scanning and decreased foraging with high encounter risk, but showed no decrease in scanning with large herd size. Yearlings increased scanning and decreased feeding with small herd size, but not with high encounter risk. Adult males were least vigilant, fed most and were not influenced by encounter risk or herd size. These age-sex class differences led to significant differences in group vigilance depending on the composition of the herd. Herds with a majority of mothers were significantly more vigilant than herds with a majority of adult males. However, these differences in group vigilance had no influence on the individual scanning of females without calves. Thus, the decrease in individual scanning with herd size may depend more on changes in individual risk than on cooperative detection of predators. (C) 2003 Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据