Spatial distribution of Qinghai spruce forests and the thresholds of influencing factors in a small catchment, Qilian Mountains, northwest China

被引:14
|
作者
Yang, Wenjuan [1 ]
Wang, Yanhui [1 ]
Wang, Shunli [2 ]
Webb, Ashley A. [3 ]
Yu, Pengtao [1 ]
Liu, Xiande [2 ]
Zhang, Xuelong [2 ]
机构
[1] Chinese Acad Forestry, Res Inst Forest Ecol Environm & Protect, Beijing, Peoples R China
[2] Acad Water Resource Conservat Forests Qilian Mt G, Zhangye 734000, Peoples R China
[3] Tamworth Agr Inst, NSW Dept Primary Ind, Calala, NSW 2340, Australia
来源
SCIENTIFIC REPORTS | 2017年 / 7卷
基金
中国国家自然科学基金;
关键词
HEIHE RIVER-BASIN; PICEA-CRASSIFOLIA; SOIL-MOISTURE; VEGETATION; TRANSPIRATION; ENVIRONMENT; PATTERNS; AREAS;
D O I
10.1038/s41598-017-05701-6
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Forest restoration in dryland mountainous areas is extremely difficult due to dry climate, complex topography and accelerating climate change. Thus, exact identification of suitable sites is required. This study at a small watershed of Qilian Mountains, Northwest China, aimed to determine the important factors and their thresholds limiting the spatial distribution of forests of Qinghai spruce (Picea crassifolia), a locally dominant tree species. The watershed was divided into 342 spatial units. Their location, terrain and vegetation characteristics were recorded. Statistical analysis showed that the potential distribution area of Qinghai spruce forests is within an ellipse with the axes of elevation (from 2673.6 to 3202.2 ma.s.l.) and slope aspect (from -162.1 degrees to 75.1 degrees deviated from North). Within this ellipse, the forested sites have a soil thickness >= 40 cm, and slope positions of lower-slope, loweror middle-slope, anywhere if the elevation is <2800, 2800-2900, >2900 ma.s.l, respectively. The corresponding mean annual air temperature at upper elevation boundary is -2.69 degrees C, while the mean annual precipitation at lower elevation boundary is 374 (331) mm within the small watershed (study area). The high prediction accuracy using these 4 factors can help to identify suitable sites and increase the success of afforestation.
引用
收藏
页数:12
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