Investigation and Analysis of Chinese(Tibetan)Medicinal Plant Resources in Shuanghu County,Tibet Autonomous Region
The medicinal plant resources were investigated in Shuanghu county of Tibet Autonomous Region to provide scientific guidance for the pro-tection and rational development and utilization of the medicinal plant resources in the county.Guided by the technical specification of traditional Chi-nese medicine resources survey,the current situation of Chinese(Tibetan)medicine resources in Shuanghu county was clarified through field sample investigation,specimen collection and production,census data collation and interview investigation,and the survey results were classified and ana-lyzed.Results showed that a total of 36 sample plots,180 quadrat sets and 1080 quadrats were surveyed in Shuanghu county.A total of 179 species of wild medicinal plants were collected,belonging to 35 families and 97 genera,including 173 species of herbs and 6 species of shrubs.The most widely distributed families were Compositae and Leguminosae,and the dominant genera were Saussurea DC.and Potentilla.Most of the medicinal parts were whole herbs,accounting for 52%.The main effects are divided into 14 categories,including heat clearing,anti-inflammatory,cough re-lieving,analgesic and bone setting drugs,of which heat clearing medicinal plants are the most.Among the collected medicinal plants,there are 1 na-tional key variety,65 commonly used Tibetan medicinal plant varieties,and 10 national key protected,rare and endangered plants.Shuanghu county is rich in wild medicinal herb resources and the grassland ecological region closest to the original natural state.However,due to the increase of human activities and the development of tourism and animal husbandry,the grassland has signs of degradation and desertification.However,the reserves of medicinal plants are small,and they cannot be commercialized.It is suggested that Shuanghu county should focus on ecological restoration and carry out scientific and reasonable protection for resources.
NETL
NSTL
万方数据
维普
