摘要
【目的】分析影响川梨分布的主导气候因子及不同时期的潜在分布。【方法】基于MaxEnt模型结合ArcGIS软件对川梨自冰期以来不同时期的分布进行预测。【结果】在末次盛冰期川梨适生区主要位于云南省、西藏东南部、四川东南部、贵州西部和广西西部地区,总面积约为96.31万km^(2)。随历史气候的变迁,川梨由末次盛冰期经全新世中期进入当代,分布区面积呈现先下降后上升的趋势。当代川梨主要分布于云南北部、四川南部、贵州西部和西藏东南部等地,适生区总面积约为74.03万km^(2)。在未来(2070 s)气候情境下,川梨潜在适宜分布区与当代相比有所增加,总面积为82.99万km^(2),增加12.10%,其中低适宜生境向西藏、四川西北部地区扩张,云南南部的高适宜区收缩明显,仅在少数地区轻微扩张。采用刀切法筛选出影响种群分布变化的4个主导气候因子及变化区间,即气温季节性变化在4000~5200,最暖季降水量在550~1000 mm,等温性>42%,最暖季平均温度11^(2)3℃。【结论】利用MaxEnt模型模拟各气候因子对川梨地理分布的影响表明,季节性气候变化是影响川梨分布的主导气候因子,另外最暖季降水量、等温性和最暖季平均温度也起了重要作用,而相对于水分,温度对种群分布的影响更大。川梨所在的横断山脉、云贵高原等地区拥有高度的地形异质性,湿度变化较小,而且在中国南方亚热带地区,可能由于气流运动形成丰富的山地降水,山地地表的水热条件仍然适宜森林植被生长,从而使川梨在复杂的山区地形和温和的微环境下保存下来,并未受到冰期的不利影响或限制作用。
【Objective】This study aimed to predict the distribution of Pyrus pashia in the last glacial maximum period,the mid-holocene period,the modern period and in the future(in the year of 2070)based on the Maxent model,and to calculate the suitable habitat areas under different climate conditions,combined with geographic information system(GIS)for visual expression.【Methods】The extensive retrieval of detailed distribution records of P.pashia in China was conducted via the Global Biodiversity Information Platform(GBIF,https://www.gbif.org/),the China Digital Plant Herbarium(CVH,http://v5.cvh.org.cn/)and other relevant online databases,to obtain the distribution data of P.pashia in China.6 climate and environmental data were obtained by accessing the World Climate Database(http://www.worldclim.org/),and the distribution points of P.pashia data and environmental variable data were imported into MaxEnt software separately and visualized with geographic information system(GIS)to predict the distribution of P.pashia under different climate conditions.【Results】The high suitable areas of P.pashia during last glacial maximum were mainly distributed in Yunnan,Eastern Tibet,Southern and Eastern Sichuan,Western Guizhou and Western Guangxi.The total suitable area was963100 km^(2),the high,medium and low suitable habitats was 482800 km^(2),220100 km^(2)and 260300 km^(2),respectively.From the last glacial maximum to the mid-holocene,the suitability area sharply decreased.Compared with the last glacial maximum,the high-suitable area in the Southern Yunnan became medium-suitable area,the high suitable area in the Eastern Sichuan disappeared,and the high suitable area in Guizhou and Guangxi also decreased or even disappeared.The total suitable area was 590200 km^(2),the high,medium and low suitable habitats were 291700 km^(2),163900 km^(2)and 145500 km^(2),respectively.From the mid-Holocene to nowadays,the suitability areas gradually increased.Compared with the midHolocene,the high suitable area was mainly concentrated in the Nnorthern Yunnan,Southern Sichuan,Western Guizhou and Eastern Tibet.The total area of the suitable habitats was 740300 km^(2),the high,medium and low suitable habitats were 351300 km^(2),191200 km^(2)and 197800 km^(2)respectively.From the now to the future,the suitable area would gradually increase.Compare with nowt,the high suitable areas were mainly concentrated in the Northern Yunnan,Southern Sichuan,Western Guizhou and Eastern Tibet.The total area of suitable habitats was 829900 km^(2),and the high,medium and low suitable habitats were 351300 km^(2),212200 km^(2),271000 km^(2),respectively.The Jackknife method was used to screen out the main environmental factors affecting the distribution of P.pashia from the 6 bioclimatic indicators.Among them,temperature seasonality(Bio4)had the largest contribution rate,reaching46.3%,indicating that the temperature seasonality would play a leading role in the potential geographical distribution pattern of P.pashia.The precipitation of warmest quarter(Bio18)contribution rate was24.8%,Isothermality(Bio3)contribution rate was 16.3%,and mean temperature of warmest quarter(Bio10)contribution rate was 10%,indicating that these three environmental factors might also play a certain role in the geographical distribution pattern of P.pashia.According to the response curve of the dominant environmental variables,when the probability of existence was over 0.5,the corresponding ecological factor value would be more suitable for the growth of P.pashia.The temperature seasonality suitable for the survival of P.pashia was 4000-5200,and the precipitation of warmest quarter was 550-1000 mm,the Isothermality was>42%,and the mean temperature of warmest quarter was 11-23℃.【Conclusion】The temperature seasonality would be the dominant climatic factor affecting the distribution of P.pashia.In addition,the precipitation of warmest quarter,isothermality and annual precipitation might also play an important role in the distribution of P.pashia.Compared with water,temperature would have a greater impact on population distribution.In this study,the total distribution area of P.pashia during the last glacial maximum increased by 30.09%,and the distribution center was 0.14°lower in latitude than that in modern time,indicating that P.pashia might be not directly affected by glaciers during the last glacial maximum.This might have a high degree of topographic heterogeneity with the Sichuan Liangshan,Yunnan-Guizhou Plateau and other regions where P.pashia was located.With small changes in humidity,the subtropical zone in the Suthern China is located in the junction of the subtropical and tropical regions,which might be due to airflow movement,precipitation,the water and heat conditions on the mountain surface suitable for the growth of forest vegetation.Therefore,P.pashia could be preserved in situ under the complex mountain terrain and mild microenvironment,with no adverse affection by the ice age or restrictive effect.
作者
刘超
董星光
田路明
霍宏亮
徐家玉
齐丹
张莹
张思梦
杨祥
郭瑞
聂晗宇
曹玉芬
LIU Chao;DONG Xingguang;TIAN Luming;HUO Hongliang;XU Jiayu;QI Dan;ZHANG Ying;ZHANG Simeng;YANG Xiang;GUO Rui;NIE Hanyu;CAO Yufen(Institute of Pomology,Chinese Academy of Agricultural Sciences,Xingcheng 125100,Liaoning,China)
出处
《果树学报》
CAS
CSCD
北大核心
2022年第11期2056-2063,共8页
Journal of Fruit Science
基金
现代农业产业技术体系建设专项(CARS-28-01)
中国农业科学院科技创新工程项目(CAAS-ASTIP)。
关键词
川梨
最大熵模型
气候变化
Pyrus pashia
Maxent model
Climate change
