Plant species diversity of wetland-dry grassland ecosystem: Taking Yanchi County, Ningxia Hui Autonomous Region as an example
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Graphical Abstract
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Abstract
In order to study the changes along the biotope gradient and influencing factors to the plant species diversity in the ecotone of wetland and dry grassland ecosystem,sample line approach had been used along wetland-dry grassland biotope gradient and samples were located in four directions: east,northeast,west and northwest,and 123 sample plots were investigated in the four sample lines.With the help of computer software such as BioDiversity Pro,the biodiversity software and Microcal Origin,the statistical software and combining measurement of species diversity indices,this study analyzed and compared species diversity of wetland-dry grassland ecosystem in Yanchi County, Ningxia Hui Autonomous Region.The results showed that the same sample line in different zone of vegetation(divided into wet strip,ecotone strip and dry strip called "three strip") had obvious differences in species diversity. Whether R,the species richness index showing species amount and abundance, or Y,the comprehensive index of species diversity,both explained that the ecotone strip was of obvious predominance,which was a reflection of marginal effects.The evenness degree index in the dry strip was bigger than the one in the ecotone strip.This coincided with the reversal of desertification,the recovery of vegetation and the formation of the predominant communities.Measurements of species diversity of four sample lines showed that the northeastern and eastern sample lines had little artificial disturbance and smaller terrain movements.This indicates that the ecotone strip maintains greater substance,energy and information flows and that every diversity index in the northeastern and eastern sample lines has values above the other two sample lines.Especially the Simpson comprehensive diversity index D of the northeast sample line is 39.92% bigger than that of the northwest sample line,which is the smallest index.
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