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Estimation of the Population Dynamics of Taxus cuspidata by Using a Static Life Table for Its Conservation
Taxus cuspidata is a rare and endangered plant species with an extremely small population which is endemic to China. This study focused on the natural T. cuspidata population in Jilin Province in China. Conventional population ecology survey methods were used to describe its population structure characteristics. Then, we chose diameter structure instead of temporal structure to establish a static population life table, draw a population survival curve, and quantify the future development trend by using population dynamic analysis and time sequence prediction. The results showed that: (1) the static life table suggested that the population of T. cuspidata was stable overall. The population survival curve tended to be Deevey Ⅱ, with a high early seedling mortality, and the later population growth tended to be stable; (2) the survival curve suggested that the population initially experienced higher mortality rates in the early stage. However, as time progressed and the population aged, the mortality rates decreased, resulting in a more stable population in the middle and late stages; (3) The diameter class structure of T. cuspidata was stable overall, and the dynamic indices showed that the population was fluctuating. The population was influenced by external disturbances and showed some resistance to human disturbance; (4) time sequence prediction analysis showed that the mortality rate of young individuals was high, natural renewal could be maintained, and the population size would remain at a certain amount in the future. The result shows that the Jilin region is a highly suitable area for the growth of Taxus cuspidata’s population in Northeast China. We recommend in situ conservation of remaining wild populations, relocation of germplasm resources, and reduction of human activities; these actions will be beneficial to Taxus cuspidata’s long-term survival.
Estimation of the Population Dynamics of Taxus cuspidata by Using a Static Life Table for Its Conservation
Taxus cuspidata is a rare and endangered plant species with an extremely small population which is endemic to China. This study focused on the natural T. cuspidata population in Jilin Province in China. Conventional population ecology survey methods were used to describe its population structure characteristics. Then, we chose diameter structure instead of temporal structure to establish a static population life table, draw a population survival curve, and quantify the future development trend by using population dynamic analysis and time sequence prediction. The results showed that: (1) the static life table suggested that the population of T. cuspidata was stable overall. The population survival curve tended to be Deevey Ⅱ, with a high early seedling mortality, and the later population growth tended to be stable; (2) the survival curve suggested that the population initially experienced higher mortality rates in the early stage. However, as time progressed and the population aged, the mortality rates decreased, resulting in a more stable population in the middle and late stages; (3) The diameter class structure of T. cuspidata was stable overall, and the dynamic indices showed that the population was fluctuating. The population was influenced by external disturbances and showed some resistance to human disturbance; (4) time sequence prediction analysis showed that the mortality rate of young individuals was high, natural renewal could be maintained, and the population size would remain at a certain amount in the future. The result shows that the Jilin region is a highly suitable area for the growth of Taxus cuspidata’s population in Northeast China. We recommend in situ conservation of remaining wild populations, relocation of germplasm resources, and reduction of human activities; these actions will be beneficial to Taxus cuspidata’s long-term survival.
Estimation of the Population Dynamics of Taxus cuspidata by Using a Static Life Table for Its Conservation
Dan Liu (author) / Zhongling Guo (author) / Xiaoyang Cui (author) / Chunnan Fan (author)
2023
Article (Journal)
Electronic Resource
Unknown
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