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出 处:《计算机应用研究》2014年第3期747-752,共6页Application Research of Computers
基 金:国家自然科学基金资助项目(11271163);国家环保部环保公益性行业科研专项基金资助项目(200909070)
摘 要:以1981—1990年我国东北地区繁殖的候鸟野生丹顶鹤为例,调查其繁殖地分布区域内的月平均气温、月平均最高温度、月平均最低温度、月平均降水和月平均净辐射五个气候因子数据的基础上,采用分区间统计及基于归一化距离的分层聚类和聚类融合等理论和方法进行相关气候数据的特征分析,获得丹顶鹤在东北繁殖地的最适宜栖息时间为5~9月份。这一结果与东北地区丹顶鹤的生物学和生态学特征相吻合。与以往文献中用于物种分布预测的气候因子提取方法不同的是,该方法完全依赖于预测物种在调查分布区内的气候数据,通过数据挖掘与数据处理而获得,而不是通过预测物种的生物学与生态学特征及其在分布区内的气候因子相关性分析得到。这一研究方法具有一般性,将为未来气候变化对候鸟在东北地区栖息地的影响的研究提供基础。Based on the five climatic factors such as monthly mean temperature, monthly mean maximum temperature, month- ly average lowest temperature, the average monthly net radiation and the monthly mean precipitation in the breeding distribu- tion area of the typical migratory species such as red-crowned crane in Northeast China from 1981 to 1990, this paper studied the characteristics analysis on the related climate data by using the theory and methods of interval statistics, hierarchical clus- tering based on normalization distance and clustering fusion technology. The results show that the most appropriate time in breeding habitat was May to September. The conclusion coincided with the biological characteristics and ecological characteris- tics of red-crowned crane in Northeast China. Extracting climatic factors from climate data was critical to the predictive distri- bution of species. The used climatic factors in the past mostly depended on the biological and ecological characteristics of spe- cies and the correlation analysis for climatic factors in the distribution area of species. Instead, this method only depended on climate data in the distribution area of the predictive species entirely, and it obtained data mining and data processing. This set of research methods possess generality and will provide basis for the research about the impact of future climate change on the predictive distribution of the migratory species in Northeast China.
关 键 词:丹顶鹤 气候因子 归一化距离 分层聚类 聚类融合
分 类 号:TP391[自动化与计算机技术—计算机应用技术] O29[自动化与计算机技术—计算机科学与技术]
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