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- W4308271341 abstract "Abstract Sambucus javanica Blume. is a Chinese native medicinal plant with high medicinal value. In this study, the MaxEnt model was used to explore the relationship between the geographical distribution of S. javanica and environmental factors, and to construct the distribution pattern of S. javanica under different climate scenarios. The results showed that the environmental conditions suitable for the distribution of S. javanica were as follows: precipitation in June ranged from 156.36 mm to 383.25 mm; solar radiation in December ranged from 6750.00 kJ·m-2·day-1 to 10521.00 kJ·m-2·day-1; isothermality ranged from 24.06 to 35.50; precipitation of warmest quarter ranged from 447.92 mm to 825.00 mm. Among them, precipitation and temperature were the key environmental factors affecting the distribution patterns of S. javanica. This plant could grow well mainly in two regions in China, covering a total area of 2.73 × 106 km2. The first region mainly consists of Guizhou, western Hubei, southeastern Chongqing, southwestern Hunan, northern Guangxi, and a small part of eastern Yunnan. The second region mainly consists of Zhejiang, southern Anhui, and northern Fujian. Under the future SSP126 and SSP585 scenarios, potentially suitable habitats in the eastern part of the potential distribution of S. javanica (Jiangxi, Fujian, Zhejiang, and Anhui) might be at risk of habitat fragmentation. Based on the result of this study, Real-time monitoring of wild groups of S. javanica is now recommended to protect its genetic diversity. These findings are supposed to promote the effective conservation and utilization of S. javanica in the future." @default.
- W4308271341 created "2022-11-10" @default.
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- W4308271341 date "2022-11-04" @default.
- W4308271341 modified "2023-10-18" @default.
- W4308271341 title "Construction of an Ecological Model of Sambucus javanica Blume in China under Different Climate Scenarios Based on Maxent model" @default.
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- W4308271341 doi "https://doi.org/10.21203/rs.3.rs-2222069/v1" @default.
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