Predictive Modeling of Suitable Habitats for Cinnamomum Camphora (L.) Presl Using Maxent Model under Climate Change in China

Lei Zhang, Zhinong Jing, Zuyao Li, Yang Liu and Shengzuo Fang
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Lei Zhang: College of Forestry, Nanjing Forestry University, Nanjing 210037, China
Zhinong Jing: College of Water Conservancy and Ecological Engineering, Nanchang Institute of Technology, Nanchang 330099, China
Zuyao Li: College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
Yang Liu: College of Forestry, Nanjing Forestry University, Nanjing 210037, China
Shengzuo Fang: College of Forestry, Nanjing Forestry University, Nanjing 210037, China

IJERPH, 2019, vol. 16, issue 17, 1-16

Abstract: Rapid changes in global climate exert tremendous pressure on forest ecosystems. Cinnamomum camphora (L.) Presl is a multi-functional tree species, and its distribution and growth are also affected by climate warming. In order to realize its economic value and ecological function, it is necessary to explore the impact of climate change on its suitable habitats under different scenarios. In this experiment, 181 geographical distribution data were collected, and the MaxEnt algorithm was used to predict the distribution of suitable habitats. To complete the simulation, we selected two greenhouse gas release scenarios, RCP4.5 and RCP8.5, and also three future time periods, 2025s, 2055s, and 2085s. The importance of environmental variables for modeling was evaluated by jackknife test. Our study found that accumulated temperature played a key role in the distribution of camphor trees. With the change of climate, the area of suitable range will increase and continue to move to the northwest of China. These findings could provide guidance for the plantation establishment and resource protection of camphor in China.

Keywords: climate change; Cinnamomum camphora (L.) Presl; distribution of habitats; MaxEnt; jackknife test (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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