Estimating the Potential Impacts of Climate Change on the Spatial Distribution of Garuga forrestii, an Endemic Species in China

Understanding how species have adapted and responded to past climate provides insights into the present geographical distribution and may improve predictions of how biotic communities will respond to future climate change. Therefore, estimating the distribution and potentially suitable habitats is essential for conserving sensitive species such as Garuga forrestii W.W.Sm., a tree species endemic to China. The potential climatic zones of G. forrestii were modelled in MaxEnt software using 24 geographic points and nine environmental variables for the current and future (2050 and 2070) conditions under two climate representative concentration pathways (RCP4.5 and RCP8.5) scenarios. The resulting ecological niche models (ENMs) demonstrated adequate internal assessment metrics, with all AUC and TSS values being >0.79 and a pROC of >1.534. Our results also showed that the distribution of G. forrestii was primarily influenced by temperature seasonality (% contribution = 12%), elevation (% contribution = 27.5%), and precipitation of the wettest month (% contribution = 35.6%). Our findings also indicated that G. forrestii might occupy an area of 309,516.2 km(2) in southwestern China. We note that the species has a potential distribution in three provinces, including Yunnan, Sichuan, and Guangxi. A significant decline in species range is observed under the future worst case of high-emissions scenario (RCP8.5), with about 19.5% and 20% in 2050 and 2070, respectively. Similarly, higher elevations shift northward to southern parts of Sichuan province in 2050 and 2070. Thus, this study helps highlight the vulnerability of the species, response to future climate and provides an insight to assess habitat suitability for conservation management.

Automated summary

Understanding how species like Garuga forrestii have adapted to past climates provides insights into present distribution and future responses to climate change. Factors such as temperature seasonality, elevation, and precipitation of the wettest month significantly influence the species distribution, with potential threats under high-emissions scenarios in the future.