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Prediction of Potentially Suitable Distribution Areas for Prunus tomentosa in China Based on an Optimized MaxEnt Model
Prunus tomentosa (Thunb.) Wall has high nutritional value and medicinal effects. It is widespread in China; however, most plants growing in the wild are near extinction in many places. Predicting the potential distribution of P. tomentosa under climate change is helpful for cultivating and protecting wild germplasm resources. We used two general circulation models (CCSM4 and MIROC-ESM) and two future climate scenarios (RCP4.5 and RCP8.5) to predict P. tomentosa’s present and future geographical distribution. A total of 137 distribution data points and 19 bioclimatic variables were imported into the maximum entropy model (MaxEnt). The optimal parameter combination (feature class LQHPT, regularized multiplier 3.0) was selected with corrected Akaike Information Criterion as the index. The results showed that at present and in the future, P. tomentosa was distributed across the northern provinces, with Gansu, Shanxi, Shaanxi, and Henan being the most suitable regions. Compared with the current climatic conditions, the potential growing area of P. tomentosa will move north, and the growing area will increase, especially in Xinjiang, where the low-impact zone area decreases. Temperature and humidity were the main variables affecting the potential distribution of the plant, including the average temperature in the coldest season (Bio11) and precipitation in the warmest season (Bio18).
Prediction of Potentially Suitable Distribution Areas for Prunus tomentosa in China Based on an Optimized MaxEnt Model
Prunus tomentosa (Thunb.) Wall has high nutritional value and medicinal effects. It is widespread in China; however, most plants growing in the wild are near extinction in many places. Predicting the potential distribution of P. tomentosa under climate change is helpful for cultivating and protecting wild germplasm resources. We used two general circulation models (CCSM4 and MIROC-ESM) and two future climate scenarios (RCP4.5 and RCP8.5) to predict P. tomentosa’s present and future geographical distribution. A total of 137 distribution data points and 19 bioclimatic variables were imported into the maximum entropy model (MaxEnt). The optimal parameter combination (feature class LQHPT, regularized multiplier 3.0) was selected with corrected Akaike Information Criterion as the index. The results showed that at present and in the future, P. tomentosa was distributed across the northern provinces, with Gansu, Shanxi, Shaanxi, and Henan being the most suitable regions. Compared with the current climatic conditions, the potential growing area of P. tomentosa will move north, and the growing area will increase, especially in Xinjiang, where the low-impact zone area decreases. Temperature and humidity were the main variables affecting the potential distribution of the plant, including the average temperature in the coldest season (Bio11) and precipitation in the warmest season (Bio18).
Prediction of Potentially Suitable Distribution Areas for Prunus tomentosa in China Based on an Optimized MaxEnt Model
Bo Fang (author) / Qian Zhao (author) / Qiulin Qin (author) / Jie Yu (author)
2022
Article (Journal)
Electronic Resource
Unknown
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