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应用生态学报 ›› 1994, Vol. 5 ›› Issue (3): 263-268.

• 研究论文 • 上一篇    下一篇

灰喜鹊的行为生态学研究Ⅰ.生殖行为

尚玉昌, 李留彬, 王飞, 王昊   

  1. 北京大学生命科学学院, 北京 100871
  • 收稿日期:1993-05-19 修回日期:1994-04-25 出版日期:1994-07-25 发布日期:1994-07-25
  • 基金资助:

    北京大学生命科学学院资助

Behavioural ecology of Azure-winged magpie(Cpanopica cyana) during its breeding period

Shang Yuchang, Li Liubin, Wang Fei, Wang Hao   

  1. College of Life Sciences, Peking University, Beijing 100871
  • Received:1993-05-19 Revised:1994-04-25 Online:1994-07-25 Published:1994-07-25

摘要: 在从南到北的地理分布上,灰喜鹊的繁殖期相应有所推迟。在它们的繁殖区域,人类的影响越大,其巢也建得越高、越隐蔽。这种很强的适应性使得它们在城区和近郊区能够更好地生存和繁殖。北京地区的灰喜鹊在4月中、下旬开始建巢,5月底是产卵高峰期。在孵卵期它们不断地翻动卵,以使其受热均匀。灰喜鹊对卵的数量比对卵的颜色和大小更敏感。孵卵期约15-17天,幼鸟18-20天出巢。在北京大学校园内的灰喜鹊的繁殖成功率约为69.05%.建立了灰喜鹊的发育行为谱。在繁殖期,灰喜鹊的巢彼此靠得较近,形成一个集体生殖领域,共同进行集体防御。

关键词: 行为适应, 繁殖成功率, 发育行为谱, 集体生殖领域, 集体防御, 面向对象, 决策树, 森林调查参数, SPOT5, 地上碳储量

Abstract: The breeding period of Azure-winged magpie has a delay with increasing latitude from south to north, and the position of its nests are higher from the ground and more cryptic with increasing population density. This kind of strong adaptive ability to environment make them survival and reproduction well in city and its suburbs. Azure-winged magpie in Beijing district begins to nest in the middle or late April, and reaches the top of laying-eggs period in the late May. Azure-winged magpie always turns over its eggs during incubation. When exchanging its eggs with quail's ones, it's found that Azure-winged magpie is much sensitive to egg's number than its size and color. The incubation period is 15-17 days, and the fledgelings leave their nest in 18-20 days after hatching. The successful rate of breeding in the campus of Peking University is about 69.05%. Adevelopmental ethogram of Azure-winged magpie is set up there. Their nests are dense and form a collective breeding territory. They are cooperative efforts in defence of a breeding territory.

Key words: Behavioural adaptation, Successful rate of breeding, Developmental ethogram, Breeding territory, Cooperative defence, SPOT5., object-based method, forest inventory parameter, decision tree, aboveground carbon storage