Applying Biomod2 for modeling of species suitable habitats:a case study of Paeonia lactiflora in China / 中国中药杂志

Paeonia lactiflora is an important medicinal resource in China. It is of great significance for the protection and cultivation of P. lactiflora resources to find the suitable habitats. The study was based on the information of 98 distribution sites and the data of 20 current environmental factors of wild P. lactiflora in China. According to the correlation and importance of environmental factors, we selected the main environmental factors affecting the potential suitable habitats. Then, BCC-CSM2-MR model was employed to predict the distribution range and center change of potential suitable habitat of wild P. lactiflora in the climate scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 during 2021-2100. The ensemble model combined with GBM, GLM, MaxEnt, and RF showed improved prediction accuracy, with TSS=0.85 and AUC=0.95. Among the 20 environmental factors, annual mean temperature, monthly mean diurnal range of temperature, temperature seasonality, mean temperature of the warmest quarter, precipitation of the wettest month, precipitation seasonality, precipitation of the driest quarter, and elevation were the main factors that affected the suitable habitat distribution of P. lactiflora. At present, the potential suitable habitats of wild P. lactiflora is mainly distributed in Inner Mongolia, Heilongjiang, Jilin, Liaoning, Hebei, Beijing, Shaanxi, Shanxi, Shandong, Gansu, Xinjiang, Tibet, and Ningxia, and concentrated in the northeastern Inner Mongolia, central Heilongjiang, and northern Jilin. Under future climate conditions, the highly sui-table area of wild P. lactiflora will shrink, and the potential suitable habitat will mainly be lost to different degrees. However, in the SSP5-8.5 scenario, the low suitable area of wild P. lactiflora will partially increase in the highlands and mountains in western China including Xinjiang, Tibet, and Qinghai during 2061-2100. The distribution center of wild P. lactiflora migrated first to the northeast and then to the southwest. The total suitable habitats were stable and kept in the high-latitude zones. The prediction of the potential geo-graphical distribution of P. lactiflora is of great significance to the habitat protection and standardized cultivation of this plant in the future.

Asian Ethnic Group Classification Model Using Data Mining / 대한법의학회지

In addition to identifying genetic differences between target populations, it is also important to determine the impact of genetic differences with regard to the respective target populations. In recent years, there has been an increasing number of cases where this approach is needed, and thus various statistical methods must be considered. In this study, genetic data from populations of Southeast and Southwest Asia were collected, and several statistical approaches were evaluated on the Y-chromosome short tandem repeat data. In order to develop a more accurate and practical classification model, we applied gradient boosting and ensemble techniques. To infer between the Southeast and Southwest Asian populations, the overall performance of the classification models was better than that of the decision trees and regression models used in the past. In conclusion, this study suggests that additional statistical approaches, such as data mining techniques, could provide more useful interpretations for forensic analyses. These trials are expected to be the basis for further studies extending from target regions to the entire continent of Asia as well as the use of additional genes such as mitochondrial genes.