摘要
2010年7—9月(雨季)和2010年11月—2011年2月(旱季),在广西弄岗国家级自然保护区采用样线法和样方法对弄岗穗鹛(Stachyris nonggangensis)觅食地选择进行研究。主成分分析表明,雨季的乔木层因素和落叶及草本层因素、旱季的地形地貌因素以及草本与灌木层因素是其觅食地的主要特征。圆形分布统计分析显示,雨季和旱季其觅食地多位于中缓坡。与对照样方的差异性检验显示,弄岗穗鹛雨季偏好乔木盖度低的生境,旱季则偏好中、下坡位、灌木高度较高且落叶厚度大的生境。两个季节觅食地的比较显示,其旱季觅食地处于较低海拔,且多位于中、下坡位;旱季草本盖度小于雨季,而落叶盖度和落叶厚度则大于雨季。逻辑斯蒂回归分析表明:弄岗穗鹛雨季觅食地选择以海拔、坡度以及落叶盖度等3个变量为综合考量,而旱季则以坡位、乔木盖度、草本盖度以及落叶厚度等4个变量为综合考量。
We investigated the feeding sites of the Nonggang Babbler (Stachyris nonggangensis) during three time periods (July-September, 2010; November-December, 2010; January-February, 2011) in Nonggang National Nature Reserve, Guangxi, China with the line transect method and sampling method. Principal component analysis of the data identified that the feeding sites in the rainy season were dominated by factors consisting of tree layer, the layer of fallen leaves and the herb layer; whereas the feeding sites in the dry season were dominated by factors dependant on terrain, herb layer and shrub layer. The results of a circular distribution analysis showed that the Nonggang Babbler preferred feeding sites with a gentle slope in both the rainy season and dry season. The tests of differences of the variables between used and control plots indicated that with low arbor coverage in the rainy season, whereas with a low slope position, high shrub and thick fallen leaves in the dry season. In comparison with the rainy season, the feeding sites in the dry season tended to be at lower altitude, to have a lower slope position, lower grass coverage, and to be covered with a larger and thicker bed of fallen leaves. A logistic regression analysis suggested that altitude, slope, and shatter cover were the most important factors influencing feeding site selection in the rainy season. Slope position, arbor cover, grass cover, and the thickness of the shatter cover were the most important factors influencing feeding site selection in the dry season.
基金
国家自然科学基金(30970381)
广西自然科学基金(2010GXNSFB013044)资助项目
关键词
弄岗穗鹛
觅食地选择
因子分析
逻辑斯蒂回归分析
Nonggang Babbler (Stachyris nonggangensis)
Feeding-site selection
Factor analysis
Logistic regression analysis