Analysis of species diversity and change characteristics of understory vegetation of different forest types in three forset regions
To explore the species diversity and change characteristics of understory vegetation of different forest types in Guangdong Province,the Eucalyptus urophylla forests of different ages(2.5,4 and 7 years old)in Jiangmen,Pinus massoniana(4 years old)and Eucalyptus urophylla forests(4.5 years old),and subtropical evergreen broad-leaved forests in Gaoming,as well as primary forests in Nanling were surveyed.Vascular plant species and their numbers in each site,calculated α-diversity indices,and assessed species importance values were recorded.Medicinal plant species,proportions,life forms,and plant parts used were also analyzed.Results indicated that:(1)In Jiangmen's Eucalyptus urophylla forests,species richness,Margalef's richness index,Shannon-Wiener index,and Fisher's α index initially decreased with forest age,then increased,while Pielou's index and Simpson dominance index showed the opposite trend.Species richness,Margalef's index,and Fisher's α index were highest in Nanling's primary forest,followed by Gaoming and Jiangmen forests.(2)Dicranopteris pedata was found in the understory dominant plants of different forest types in the three forest regions.The top five important understory plants were most dominant in Jiangmen's Eucalyptus urophylla forests and least in Nanling's primary forests,where plant distribution was more even.(3)Gaoming had the highest diversity of medicinal plant species among the forest types.From Eucalyptus urophylla forests in Jiangmen to primary forests in Nanling,the predominant life form of medicinal plants shifted from annual herbs to evergreen broad-leaved trees,and the plant parts used shifted from whole plants to leaves and roots.This study highlights the significant influence of forest age on understory plant diversity in Eucalyptus urophylla forests.As forest complexity increases,both the richness and evenness of understory plants and medicinal species distribution improve.
NETL
NSTL
万方数据
