Shi Jingye, Xia Muxuan, He Guoqin, Gonzalez Norela C T, Zhou Sheng, Lan Kun, Ouyang Lei, Shen Xiangbao, Jiang Xiaolong, Cao Fuliang, Li He
College of Forestry, Central South University of Forestry and Technology, Changsha, 410004, Hunan, China.
Bangor College China, a Joint Unit of Bangor University and Central South University of Forestry and Technology, Changsha, 410004, Hunan, China.
J Environ Manage. 2024 Apr;357:120841. doi: 10.1016/j.jenvman.2024.120841. Epub 2024 Apr 6.
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.
黧蒴栲是青冈属的一种常绿乔木,是东亚亚热带地区具有生态和经济价值的物种。预测气候变化对黧蒴栲潜在分布的影响,可为其遗传资源的保护和利用以及造林提供科学依据。本研究通过数据收集和处理,获取了74条黧蒴栲分布记录和9个气候变量。从WorldClim下载的当前气候数据以及主要基于分布地点温室气体排放预测的四种未来气候情景(2040年代SSP1-2.6、2040年代SSP5-8.5、2060年代SSP1-2.6和2060年代SSP5-8.5)的未来气候数据,被用于具有优化参数的MaxEnt模型中,以预测黧蒴栲的分布动态及其对气候变化的响应。结果表明,预测的当前分布与黧蒴栲的自然分布一致,其主要分布在中国的湖南、江西、浙江、福建、贵州和台湾省,以及日本和韩国济州岛。在当前气候条件下,降水因素对黧蒴栲分布的影响比温度因素更为显著,最干季度降水量(BIO17)是其当前分布的最重要限制因素(贡献率为57.35%)。在未来气候条件下,最干季度平均温度(BIO9)是影响黧蒴栲未来潜在分布变化的关键气候因素。随着未来气候异常程度的增加,黧蒴栲预测分布总面积呈缩小趋势(减少12.24%-45.21%),且黧蒴栲将向高海拔和高纬度地区迁移。研究结果阐明了黧蒴栲的潜在分布范围和适宜气候条件,可为黧蒴栲及其他相关物种的保护、开发和利用提供重要的理论参考。