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生态学杂志 ›› 2023, Vol. 42 ›› Issue (11): 2638-2645.doi: 10.13292/j.1000-4890.202311.012

• 研究报告 • 上一篇    下一篇

气候因子对黑龙江省茶藨子属植物地理分布格局的影响


赵文博1,吴立仁2,郭佰涛1,张磊1,周双1,周春薇1,房磊1,李鹏举1,刘佳3,段亚东1,4*


  

  1. 1黑龙江省农业科学院乡村振兴科技研究所, 哈尔滨 150028; 2黑龙江省农业科学院经济作物研究所, 哈尔滨 150086; 3黑龙江省绥棱县农业技术推广中心, 黑龙江绥化 152200; 4农业农村部园艺作物种质资源利用重点实验室, 辽宁兴城 125100)

  • 出版日期:2023-11-10 发布日期:2023-10-27

Effects of climate factors on geographical distribution patterns of Ribes species in Heilongjiang, China.

ZHAO Wenbo1, WU Liren2, GUO Baitao1, ZHANG Lei1, ZHOU Shuang1, ZHOU Chunwei1, FANG Lei1, LI Pengju1, LIU Jia3, DUAN Yadong1,4*#br#

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  1. (1Institute of Science and Technology for Rural Revitalization, Heilongjiang Academy of Agricultural Sciences, Harbin 150028, China; 2Institute of Industrial Crop, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China; 3Agricultural Technology Extension Center of Suiling County, Suihua 152200, Heilongjiang, China; 4Key Laboratory of Horticultural Crops Germplasm Resources Utilization, Ministry of Agriculture and Rural Affairs, Xingcheng 125100, Liaoning, China).

  • Online:2023-11-10 Published:2023-10-27

摘要: 在影响植物分布的诸多因素中,气候因子是最主要的因素。为探究气候因子对茶藨子属(Ribes)植物在黑龙江省分布格局的影响,本研究以6种茶藨子属植物为对象,利用ArcGIS技术,根据茶藨子属植物在黑龙江省地理分布点的经纬度信息和从WorldClim数据库中提取各分布点气候数据,采用核密度分析、MaxEnt模型、统计分析、线性回归方程、冗余分析以及蒙特卡洛检验等分析手段,量化各气候因子对茶藨子属植物地理分布差异的贡献大小。结果表明:(1)茶藨子属植物主要分布于黑龙江省的西北地区及东南地区,其中在西北地区分布尤为密集,具有明显的分布区重叠现象,分布区整体上具有干燥寒冷的气候特点,且MaxEnt模型预测结果与实际分布吻合。(2)降水量变异系数、等温性、年降水量、干燥度和最干月降水量主要影响黑龙江省茶藨子属植物在经度上的分布;最冷季度平均气温和最湿季度降水量主要影响黑龙江省茶藨子属植物在纬度上的分布。(3)冗余分析表明,气候因子在两轴的合计解释率为100%;蒙特卡洛检验进一步表明,对黑龙江省茶藨子属植物沿经纬度分布差异解释率最高的3个气候因子分别为:最冷季度平均气温(85.7%)、年降水量(54.2%)、最暖月最高气温(42.8%),表明这3个气候因子主导茶藨子属植物在黑龙江省的地理分布格局。


关键词: 茶藨子属, 气候因子, 地理分布格局, 冗余分析

Abstract: Climate is the most determinant one among factors shaping plant distribution. In this study, we explored the effects of climate factors on the distribution pattern of six Ribes species in Heilongjiang Province, China. Based on the latitude and longitude information of geographic distribution of six Ribes species in Heilongjiang Province, climatic data of the distribution points were extracted from WorldClim database by ArcGIS technology. The kernel density analysis, MaxEnt model, statistical analysis, linear regression equation, redundancy analysis and Monte Carlo test were used to quantify the contribution of climatic factors to their geographic distribution. The results showed that: (1) The six species were mainly distributed in the northwest and southeast regions of Heilongjiang Province, especially in the northwestern part, with obvious overlapping distribution. Natural habitats of the six species were characterized by dry and cold climatic conditions. The spatial distribution predicted by MaxEnt model was evidenced by field investigation. (2) Longitudinal distributions of the six species were mainly driven by the coefficient of variation of precipitation, isothermality, annual precipitation, aridity index, precipitation of the driest month. The latitudinal distributions, however, were mainly determined by mean temperature in the coldest quarter and precipitation in the wettest quarter. (3) Climate factors accounted for 100% of the cumulative variation of all data in the two axes. Results of Monte Carlo test further revealed the first three climatic factors with the highest explanatory powers for the distribution differences of the six Ribes species along latitude and longitude were mean temperature of the coldest quarter (85.7%), annual precipitation (54.2%), and maximum temperature of the warmest month (42.8%), indicating that these three climatic factors dominated the geographical distribution pattern of the Ribes species in Heilongjiang Province.


Key words: Ribes, climatic factor, geographical distribution pattern, redundancy analysis.