Predicting Quercus gilva distribution dynamics and its response to climate change induced by GHGs emission through MaxEnt modeling

Jingye Shi; Muxuan Xia; Guoqin He; Norela C T Gonzalez; Sheng Zhou; Kun Lan; Lei Ouyang; Xiangbao Shen; Xiaolong Jiang; Fuliang Cao; He Li

doi:10.1016/j.jenvman.2024.120841

Predicting Quercus gilva distribution dynamics and its response to climate change induced by GHGs emission through MaxEnt modeling

J Environ Manage. 2024 Apr:357:120841. doi: 10.1016/j.jenvman.2024.120841. Epub 2024 Apr 6.

Authors

Jingye Shi¹, Muxuan Xia¹, Guoqin He², Norela C T Gonzalez¹, Sheng Zhou¹, Kun Lan², Lei Ouyang³, Xiangbao Shen¹, Xiaolong Jiang¹, Fuliang Cao⁴, He Li⁵

Affiliations

¹ College of Forestry, Central South University of Forestry and Technology, Changsha, 410004, Hunan, China.
² Bangor College China, a Joint Unit of Bangor University and Central South University of Forestry and Technology, Changsha, 410004, Hunan, China.
³ Fujian Academy of Forestry, Fuzhou, 350012, Fujian, China.
⁴ Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China.
⁵ College of Forestry, Central South University of Forestry and Technology, Changsha, 410004, Hunan, China. Electronic address: lihecsuft@126.com.

PMID: 38581898
DOI: 10.1016/j.jenvman.2024.120841

Abstract

Quercus gilva, an evergreen tree species in Quercus section Cyclobalanopsis, is an ecologically and economically valuable species in subtropical regions of East Asia. Predicting the impact of climate change on potential distribution of Q. gilva can provide a scientific basis for the conservation and utilization of its genetic resources, as well as for afforestation. In this study, 74 distribution records of Q. gilva and nine climate variables were obtained after data collection and processing. Current climate data downloaded from WorldClim and future climate data predicted by four future climate scenarios (2040s SSP1-2.6, 2040s SSP5-8.5, 2060s SSP1-2.6, and 2060s SSP5-8.5) mainly based on greenhouse gases emissions of distribution sites were used in MaxEnt model with optimized parameters to predict distribution dynamics of Q. gilva and its response to climate change. The results showed that the predicted current distribution was consistent with natural distribution of Q. gilva, which was mainly located in Hunan, Jiangxi, Zhejiang, Fujian, Guizhou, and Taiwan provinces of China, as well as Japan and Jeju Island of South Korea. Under current climate conditions, precipitation factors played a more significant role than temperature factors on distribution of Q. gilva, and precipitation of driest quarter (BIO17) is the most important restriction factor for its current distribution (contribution rate of 57.35%). Under future climate conditions, mean temperature of driest quarter (BIO9) was the essential climate factor affecting future change in potential distribution of Q. gilva. As the degree of climatic anomaly increased in the future, the total area of predicted distribution of Q. gilva showed a shrinking trend (decreased by 12.24%-45.21%) and Q. gilva would migrate to high altitudes and latitudes. The research results illustrated potential distribution range and suitable climate conditions of Q. gilva, which can provide essential theoretical references for the conservation, development, and utilization of Q. gilva and other related species.

Keywords: Climate change; Greenhouse gases emission; MaxEnt model; Potential distribution; Quercus gilva; Species distribution modeling.

MeSH terms

China
Climate Change
Ecosystem
Greenhouse Gases*
Quercus*
Taiwan

Substances

Greenhouse Gases