Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmenta...Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmental factors thatcould affect the distribution of T. sutchuenensis, including climate, topography, soil and Normalized DifferenceVegetation Index (NDVI), we adopted the Random Forest-MaxEnt integrated model to analyze our data. Basedon the Random Forest study, the contribution of the mean temperature of the warmest quarter, mean temperatureof the coldest quarter, annual mean temperature and mean temperature of the driest quarter was large. Based onMaxEnt model prediction outputs, the potential distribution map not only identified areas that originallyrecorded T. sutchuenensis, such as Xuanhan County, Kai County and Chengkou County, but also identified highlysuitable distribution areas where T. sutchuenensis may exist, including Wanyuan County, Sichuan Province, andthe junction of Chongqing and Hubei Province. This provides a more explicit geographic range for ex situ conservation and reintroduction of T. sutchuenensis. Our results also indicate that, in addition to climate factors,topography and soil factors are also important environmental factors that affect distribution. This provides a theoretical basis for subsequent laboratory construction to simulate the indoor growth of T. sutchuenensis.展开更多
文摘Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmental factors thatcould affect the distribution of T. sutchuenensis, including climate, topography, soil and Normalized DifferenceVegetation Index (NDVI), we adopted the Random Forest-MaxEnt integrated model to analyze our data. Basedon the Random Forest study, the contribution of the mean temperature of the warmest quarter, mean temperatureof the coldest quarter, annual mean temperature and mean temperature of the driest quarter was large. Based onMaxEnt model prediction outputs, the potential distribution map not only identified areas that originallyrecorded T. sutchuenensis, such as Xuanhan County, Kai County and Chengkou County, but also identified highlysuitable distribution areas where T. sutchuenensis may exist, including Wanyuan County, Sichuan Province, andthe junction of Chongqing and Hubei Province. This provides a more explicit geographic range for ex situ conservation and reintroduction of T. sutchuenensis. Our results also indicate that, in addition to climate factors,topography and soil factors are also important environmental factors that affect distribution. This provides a theoretical basis for subsequent laboratory construction to simulate the indoor growth of T. sutchuenensis.
