Species resource and distribution of genus Rubus in Qinling Mountains within Shaanxi
[Objective]The study aimed to clarify the distribution pattern of the genus Rubus plants in different counties of the Qinling Mountain area of Shaanxi,identify hotspot areas,draw thematic maps based on administrative units,and to summarize and analyze their growth status and distribution in the Qin-ling Mountains.[Method]Combined with literature data,the method of field survey was used to determine the species,habitat,ornamental characteristics and spatial distribution of the genus plants.With the admin-istrative counties(districts)as the units,the county-level distribution(including county-level cities and dis-tricts)of the plants was mapped according to the method of natural intermittent point classification,fol-lowed by screening the hotspot counties of the genus plant distribution with the method of Dobson.[Result]Rubus plant are 36 species and 10 Rubus variants in Qinling,Shaanxi Province.It is widely distrib-uted at the altitude of 500～2 999 m,and the most suitable altitude is 1 500～1 999 m.The distributed hot spots are 8 counties(districts),with the south slope taking Ningshan and Shiquan as the core,and the north slope taking Taibai as the core.The intensity of differentiation is highly correlated with the species density,and the trend decreases from the higher mountains to the lower mountains;the number decreases in both sides of the region.[Conclusion]The Qinling Mountains in Shaanxi Province have a wide variety of Rubus,with rich colors and fruit colors.The main ornamental season is summer.The intensity of species differentia-tion affects the distribution pattern of species diversity to some extent,and the spatial regional pattern of Rubus plant in Qinling Mountains,Shaanxi Province is closely related to the altitude of mountains.The cli-mate and topographic conditions in Qinling Mountains of Shaanxi Province influence the county distribution pattern and differentiation strength of Rubus plant.
Qinling Mountains in ShaanxiRubusresource analysisspecies distribution
NETL
NSTL
万方数据
