ABSTRACT
Objective:To analyze the main factors affecting the <italic>Ziziphus jujuba</italic> distribution and expand the understanding of its distribution and the corresponding influencing factors by comparing the distribution sites of <italic>Z. jujuba</italic> predicted by models with those recorded in the literature. Method:More than 200 distribution sites of <italic>Z. jujuba</italic> accompanied by 55 environmental factors were obtained from literature and specimen review. The environmental factors that affect the distribution of <italic>Z. jujuba</italic> were explored by maximum entropy （MaxEnt） model， and the potential distribution areas of <italic>Z. jujuba</italic> in China were analyzed by ArcGIS， followed by the verification of the main environmental factors using receiver-operating characteristic （ROC） curve and Jackknife method. Result:The area under the curve （AUC） values for the test data and training data were both greater than 0.9， which perfectly satisfied the standard， indicating that the research results were accurate and reliable. Conclusion:The annual average temperature， the average temperature in May， the average temperature in the warmest season， vegetation type， soil type， average temperature in June， average temperature in September， and average temperature in August are proved to be the main environmental factors affecting the distribution of <italic>Z. jujuba</italic>， which can be found almost all over China， except for Heilongjiang and Tibet. <italic>Z. jujuba</italic> is most suitable to be planted in southeastern Sichuan， Chongqing， southern Gansu， Ningxia， most areas of central Shaanxi， eastern and southwestern Shanxi， Henan， eastern and northern Hubei， northern and eastern Anhui， Shandong， Hebei， Beijing， Tianjin， western Liaoning， and Zhejiang. As revealed by literature review， the most suitable growing areas of <italic>Z. jujuba</italic> are southeastern Sichuan， central Shaanxi， southwestern Shanxi， western and northern Henan， Shandong， and southwestern and eastern Hebei.
ABSTRACT
In order to study the ecology suitability of Pterocephalus hookeri, and provide a reference for GAP planting location and regional development, the Maxent model and GIS technology were used to investigate ecology suitability regions for P. hookeri based on the distribution points collected from Chinese virtual herbarium, the references and field trips. The potential distribution areas mainly concentrated in the eastern Tibet, western Sichuan, southern Qinghai, northwest Yunnan, and southern Gansu. There were 7 major environmental factors to have obvious influence on ecology suitability distributions of P. hookeri, including altitude (contribution rate of 62%), precipitation of warmest quarter (contribution rate of 14.4%), coefficient of variation of precipitation seasonality (contribution rate of 7.2%), mean temperature of driest quarter (contribution rate of 3.5%), the electrical conductivity of top and sub-soil (contribution rate of 3%), the total exchangeable bases in the top- and subsoil (contribution rate of 2.4%) and SD of temperature seasonality (contribution rate of 2.2%). The study of the ecological suitability regionalization of P. hookeri based on Maxent model can provide scientific basis for the selection of artificial planting base and GAP planting location.
ABSTRACT
Wildlife tending and artificial cultivation is an important way to protect the wild resources of Rhodiola crenulata. It is a study hotspot at present. The distribution information of R. crenulata was collected by query data and field survey, the ecological suitability regionalization was conducted based on maximum entropy model combine with ecological factors, including climate, soil and altitude. To provide the reference for production layout, suitable planting area and the selection of artificial planting base by studying the ecological suitability regionalization of R. crenulata. The potential distribution areas mainly concentrated in the easen Tibet, western Sichuan, southern Qinghai, and Gansu Gannan Tibetan Autonomous Prefecture, Yunnan Diqing Tibetan Autonomous Prefecture. There were 5 major environmental factors to have obvious influence on ecology suitability distributions of R. crenulata, including altitude (contribution rate of 61.8%), precipitation of warmest quarter (contribution rate of 19%), the coefficient of variation of precipitation seasonality (contribution rate of 4.7%), the SD of temperature seasonality (contribution rate of 4%), mean temperature of driest quarter (contribution rate of 2.5%). The AUCs of ROC curve were both above 0.9, indicating that the predictive results with the Maxent model were highly precise. The study of the ecological suitability regionalization of R. crenulata based on Maxent can provide a scientific basis for the selection of artificial planting base.