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麻花杜鹃的地理分布模拟
王 刚1, 孟艳琼1, 孙 婧1
安徽农业大学 林学与园林学院
摘要:
【目的】利用DIVA-GIS软件模拟麻花杜鹃在当前和未来的潜在分布区域,揭示影响麻花杜鹃分布的因子,为该物种的遗传多样性起源、系统进化研究和种质资源保护提供资料。【方法】全面收集麻花杜鹃的地理分布资料,基于获得的73个精确分布点信息,利用DIVA-GIS中的BIOCLIM模型对麻花杜鹃地理分布格局进行模拟和预测,绘制麻花杜鹃实际地理分布及当前和未来潜在分布区域图,并结合19个环境因子进行主成分分析, 获取影响麻花杜鹃地理分布的主要因子。【结果】麻花杜鹃在我国的分布格局为:中部较多,南部和东部也有一定的分布。通过主成分分析发现,最热月温度、温度季节变化方差和年降雨量是影响麻花杜鹃分布的主要因子。【结论】麻花杜鹃当前的潜在分布区与实际分布区有很好的一致性,当前和未来潜在分布区的一些分布点中心依然位于中部,未来分布区部分分布点向东部迁移,而西南部的一些分布点消失。应重视对麻花杜鹃潜在适生区和迁地的保护。
关键词:  麻花杜鹃  物种分布  DIVA-GIS  气候变量  BIOCLIM模型
DOI:
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基金项目:林业公益性行业科研专项(201204506);国家自然科学基金项目(31070569)
Modeling the geographic distribution of Rhododendron maculiferum
Abstract:
【Objective】DIVA-GIS software was used to simulate the current and future potential distribution area for Rhododendron maculiferum,and the factors impacting distribution of R.maculiferum were discussed.This study will help investigation on genetic diversity and origin system evolution as well as protection of germplasm resources.【Method】The spatial distribution data were collected and the obtained 73 accurate R.maculiferum information was simulated using the BIOCLIM model of DIVA-GIS software.The actual,present and future geographic distribution maps of R.maculiferum were drawn.19 environment factors were adopted for principal component analysis to get the main factors affecting the distribution of R.maculiferum.【Result】R.maculiferum mainly distributes in central,southern and eastern China.According to the principal component analysis,maximum temperature of warmest month,temperature seasonality,and annual precipitation were the dominant factors for geographic distribution of R.maculiferum.【Consultion】The results showed that present distribution matched actual distribution ranges.The present and future potential distribution areas are still in the central and have a trend to move eastward while the southwestern points will disappear.Attention should be paid to the protection of R.maculiferum.
Key words:  Rhododendron maculiferum  species distribution  geographic information system  climate variables  BIOCLIM model