Maxent Modeling for Predicting the Potential Geographical Distribution of Castanopsis carlesii under Various Climate Change Scenarios in China
نویسندگان
چکیده
Castanopsis carlesii (Hemsl.) Hayata. 1917 is an established subtropical evergreen broad-leaved tree species with rapid growth rates and a strong plasticity to environmental changes. It widely distributed in East Asia; however, it unclear how climate change influences the distribution of this species. Based on 210 valid occurrence records 10 variables, we used maximum entropy model (Maxent) predict its potential geographical under present three future scenarios (SSP126, SSP245 SSP585) both 2050s 2070s, determined influence C. carlesii. The area curve (AUC) value simulated training test were 0.949 0.920, respectively, indicating excellent forecast. main climatic factors affecting are mainly precipitation, especially that driest month (Bio14, 75.5%), annual precipitation (Bio12, 14.3%); total contribution rate 89.8%. However, impact average mean temperature lesser comparison (Bio1, 5.7%). According present-day predictions, has suitable habitat 208.66 × 104 km2 across most tropical regions south Yangtze River. medium high suitability areas Taiwan, Fujian, Jiangxi, Guangdong, Hainan Guangxi Provinces. With projected warm future, exhibited tendency northward expansion along Qinling–Huaihe line, manifested as increase low areas. high-suitable decreased significantly for only few showed contraction Therefore, can be cultivation or introduction trials, while require enhanced preservation collection genetic resources. Our findings provide theoretical basis formulating adaptation protection strategies cope well guidance introduction, sustainable development
منابع مشابه
Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination
Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. ...
متن کاملModeling Current and Future Potential Distributions of Caspian Pond Turtle (Mauremys caspica) under Climate Change Scenarios
Although turtles are the most threatened taxonomic group within the reptile class, we have a very limited understanding of how turtles respond to climate change. Here, we evaluated the effects of climate changes on the geographical distribution of Caspian pond turtle (Mauremys caspica). We used an ensemble approach by combining six species distribution models including artificial neural network...
متن کاملModeling the Potential Distribution of Bacillus anthracis under Multiple Climate Change Scenarios for Kazakhstan
Anthrax, caused by the bacterium Bacillus anthracis, is a zoonotic disease that persists throughout much of the world in livestock, wildlife, and secondarily infects humans. This is true across much of Central Asia, and particularly the Steppe region, including Kazakhstan. This study employed the Genetic Algorithm for Rule-set Prediction (GARP) to model the current and future geographic distrib...
متن کاملPredicting the Potential Distribution of Polygala tenuifolia Willd. under Climate Change in China
Global warming has created opportunities and challenges for the survival and development of species. Determining how climate change may impact multiple ecosystem levels and lead to various species adaptations is necessary for both biodiversity conservation and sustainable biological resource utilization. In this study, we employed Maxent to predict changes in the habitat range and altitude of P...
متن کاملPotential geographic distribution of Prangos ferulacea (L.) Lindl. in Chaharmahal va Bakhtiari province under climate change scenarios
Prangos ferulacea (L.) Lindl is a perennial plant that besides fodder and medicinal values the plant can help to control soil erosion. There is little knowledge about the effect of climate change on the Prangos genus especially P. ferulacea. In this study, we used ensemble modeling based on five species distribution models to predict the potential effects of climate change on the future geograp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Forests
سال: 2023
ISSN: ['1999-4907']
DOI: https://doi.org/10.3390/f14071397