气候变化下桃儿七潜在地理分布的预测

doi:10.3724/SP.J.1258.2014.00022

植物生态学报 ›› 2014, Vol. 38 ›› Issue (3): 249-261.DOI: 10.3724/SP.J.1258.2014.00022

所属专题：青藏高原植物生态学：群落生态学

气候变化下桃儿七潜在地理分布的预测

郭彦龙¹^,², 卫海燕¹^,^*(), 路春燕¹^,³, 张海龙¹, 顾蔚²^,⁴^,^*()

¹陕西师范大学旅游与环境学院, 西安 710062
²陕西师范大学西北濒危药材资源开发国家工程实验室, 西安 710062
³中国科学院东北地理与农业生态研究所, 长春 130102
⁴陕西师范大学生命科学学院, 西安 710062

收稿日期:2013-06-27 接受日期:2013-10-16 出版日期:2014-06-27 发布日期:2014-02-27
通讯作者: 卫海燕,顾蔚
作者简介:weigu@snnu.edu.cn
*E-mail: weihy@snnu.edu.cn;
基金资助:
国家自然科学基金(31070293);国家“十一五”科技支撑计划项目(2006BAI06A13-06)

Predictions of potential geographical distribution of Sinopodophyllum hexandrum under climate change

GUO Yan-Long¹^,², WEI Hai-Yan¹^,^*(), LU Chun-Yan¹^,³, ZHANG Hai-Long¹, GU Wei²^,⁴^,^*()

¹College of Tourism and Environment, Shaanxi Normal University, Xian 710062, China
²National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest of China, Shaanxi Normal University, Xian 710062, China
³Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
⁴College of Life Sciences, Shaanxi Normal University, Xian 710062, China

Received:2013-06-27 Accepted:2013-10-16 Online:2014-06-27 Published:2014-02-27
Contact: WEI Hai-Yan,GU Wei

摘要/Abstract

摘要：

桃儿七(Sinopodophyllum hexandrum)为小檗科多年生草本植物, 是我国濒危传统藏药, 预测气候变化对该物种分布范围的影响对于其保护和资源可持续利用具有重要意义。该文利用获得的桃儿七136个地理分布记录和21个气候环境图层, 通过MaxEnt模型分析桃儿七在我国西部七省的潜在地理分布, 并基于该模型预测政府间气候变化专门委员会(IPCC)发布的SRES-A1B、SRES-A2和SRES-B1气候情景下21世纪20、50和80年代桃儿七分布范围。结果表明: 最热季平均温度、年降水量、温度季节性变动系数和等温性是影响桃儿七分布的主要气候因子; 在当前气候条件下, 桃儿七适宜的生境面积占研究区总面积的11.71%, 主要集中在青藏高原东缘的四川、甘肃、青海境内次生植被丰富、地形复杂的高海拔地区, 低适宜生境与不适宜生境分别占研究区总面积的15.86%与72.43%。由模型预测可知, 在SRES-A1B、SRES-A2和SRES-B1三种情景下, 桃儿七在研究区低适宜生境的数量相对变化较小, 在适宜生境先大幅减少后又缓慢增加。研究结果同时表明, 在未来气候变化条件下, 桃儿七的适宜生境平均海拔将逐渐升高, 范围以及几何重心极有可能先向北移, 然后再向西延伸至青藏高原内部较高海拔的山区。

关键词: 气候变化, MaxEnt模型, 潜在地理分布, 桃儿七

Abstract:

Aims Specific information on geographic distribution of a species is important for its conservation. This study was conducted to determine the potential geographic distribution of Sinopodophyllum hexandrum, which is an endangered plant used in traditional Tibetan medicine, and to predict how climate change would affect its geographic range.
Methods The potential geographic distribution of S. hexandrum under the current conditions in western China was simulated with MaxEnt software based on species presence data at 136 locations and 21 climatic variables. The future distributions of S. hexandrum were also projected for the periods 2020s, 2050s and 2080s under the climate change scenarios of A1B, A2 and B1 described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change).
Important findings Results showed that mean temperature of the warmest quarter, annual precipitation, temperature seasonality, and isothermally were the four dominant climatic factors influencing the geographic distribution of Sinopodophyllum hexandrum. For the entire region of the seven provinces in western China, 11.71% of the areas were identified as suitable habitats, 15.86% as marginally suitable habitats, and 72.43% as, unsuitable habitats. The suitable habitats are mainly located in Sichuan, Gansu, Qinghai in the eastern edge of Qinghai-Xizang Plateau, and in areas with rich secondary vegetation and complex terrain in high altitudes. The model simulations indicated that the marginally suitable habitats would have a relatively small change under the climate change scenarios of SRES-A1B, SRES-A2 and SRES-B; whereas the suitable habitats would initially decrease by 2020s, followed by a trend of moderate increased thereafter. The average elevation of suitable habitats would be increased, and both the distributional range and the center of distribution would shift northward first, and then move west to the higher altitudes in mountainous areas of Qinghai-Xizang Plateau.

Key words: climatic change, MaxEnt model, potential geographic distribution, Sinopodophyllum hexandrum

郭彦龙, 卫海燕, 路春燕, 张海龙, 顾蔚. 气候变化下桃儿七潜在地理分布的预测. 植物生态学报, 2014, 38(3): 249-261. DOI: 10.3724/SP.J.1258.2014.00022

GUO Yan-Long, WEI Hai-Yan, LU Chun-Yan, ZHANG Hai-Long, GU Wei. Predictions of potential geographical distribution of Sinopodophyllum hexandrum under climate change. Chinese Journal of Plant Ecology, 2014, 38(3): 249-261. DOI: 10.3724/SP.J.1258.2014.00022

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链接本文: https://www.plant-ecology.com/CN/10.3724/SP.J.1258.2014.00022

https://www.plant-ecology.com/CN/Y2014/V38/I3/249

图/表 10

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数据简称 Code	中文名称 Chinese name	英文名称 English name
Bio1	年平均气温	Annual mean air temperature
Bio2	平均气温日较差 (平均每月最高气温-平均每月最低气温)	Mean diurnal air temperature range (Mean of monthly (maximum air temperature-minimum air temperature))
Bio3	等温性	Isothermality
Bio4	气温季节性变动系数	Air temperature seasonality
Bio5	最热月的最高气温	Max air temperature of the warmest month
Bio6	最冷月的最低气温	Min air temperature of the coldest month
Bio7	气温年较差	Air temperature annual range
Bio8	最湿季平均气温	Mean air temperature of the wettest quarter
Bio9	最干季平均气温	Mean air temperature of the driest quarter
Bio10	最热季平均气温	Mean air temperature of the warmest quarter
Bio11	最冷季平均气温	Mean air temperature of the coldest quarter
Bio12	年降水量	Annual precipitation
Bio13	最湿月降水量	Precipitation of the wettest month
Bio14	最干月降水量	Precipitation of the driest month
Bio15	降水量的季节性变化(变异系数)	Precipitation seasonality (coefficient of variation)
Bio16	最干季降水量	Precipitation of the driest quarter
Bio17	最湿季降水量	Precipitation of the wettest quarter
Bio18	最热季降水量	Precipitation of the warmest quarter
Bio19	最冷季降水量	Precipitation of the coldest quarter
ATG	生长期平均气温^*	Average air temperature of growth period^*
PG	生长期降水量^*	Precipitation of growth period^*

数据简称 Code	中文名称 Chinese name	英文名称 English name
Bio1	年平均气温	Annual mean air temperature
Bio2	平均气温日较差 (平均每月最高气温-平均每月最低气温)	Mean diurnal air temperature range (Mean of monthly (maximum air temperature-minimum air temperature))
Bio3	等温性	Isothermality
Bio4	气温季节性变动系数	Air temperature seasonality
Bio5	最热月的最高气温	Max air temperature of the warmest month
Bio6	最冷月的最低气温	Min air temperature of the coldest month
Bio7	气温年较差	Air temperature annual range
Bio8	最湿季平均气温	Mean air temperature of the wettest quarter
Bio9	最干季平均气温	Mean air temperature of the driest quarter
Bio10	最热季平均气温	Mean air temperature of the warmest quarter
Bio11	最冷季平均气温	Mean air temperature of the coldest quarter
Bio12	年降水量	Annual precipitation
Bio13	最湿月降水量	Precipitation of the wettest month
Bio14	最干月降水量	Precipitation of the driest month
Bio15	降水量的季节性变化(变异系数)	Precipitation seasonality (coefficient of variation)
Bio16	最干季降水量	Precipitation of the driest quarter
Bio17	最湿季降水量	Precipitation of the wettest quarter
Bio18	最热季降水量	Precipitation of the warmest quarter
Bio19	最冷季降水量	Precipitation of the coldest quarter
ATG	生长期平均气温^*	Average air temperature of growth period^*
PG	生长期降水量^*	Precipitation of growth period^*

地区 Region	面积百分比 Percentage of area (%)			面积 Area (km²)
地区 Region	适宜生境 Suitable habitat	低适宜生境 Marginally suitable habitat	不适宜生境 Unsuitable habitat	适宜生境 Suitable habitat	低适宜生境 Marginally suitable habitat	不适宜生境Unsuitable habitat
甘肃 Gansu	20.28	15.13	64.59	92 152.32	68 750.72	293 496.97
四川 Sichuan	18.39	26.58	55.03	88 529.46	127 956.12	264 914.42
西藏东部 Eastern Xizang	16.91	19.47	63.62	75 533.50	86 968.49	284 177.48
青海 Qinghai	7.22	10.66	82.12	52 150.06	76 997.18	593 152.75
宁夏 Ningxia	13.32	22.09	64.59	8 844.48	14 667.76	42 887.76
云南 Yunnan	1.54	12.22	86.24	5 902.82	46 839.26	330 557.91
陕西 Shaanxi	0.10	7.57	92.33	205.60	15 563.92	189 830.49
总计 Total	11.71	15.86	72.43	323 318.24	437 743.45	1 999 017.78

地区 Region	面积百分比 Percentage of area (%)			面积 Area (km²)
地区 Region	适宜生境 Suitable habitat	低适宜生境 Marginally suitable habitat	不适宜生境 Unsuitable habitat	适宜生境 Suitable habitat	低适宜生境 Marginally suitable habitat	不适宜生境Unsuitable habitat
甘肃 Gansu	20.28	15.13	64.59	92 152.32	68 750.72	293 496.97
四川 Sichuan	18.39	26.58	55.03	88 529.46	127 956.12	264 914.42
西藏东部 Eastern Xizang	16.91	19.47	63.62	75 533.50	86 968.49	284 177.48
青海 Qinghai	7.22	10.66	82.12	52 150.06	76 997.18	593 152.75
宁夏 Ningxia	13.32	22.09	64.59	8 844.48	14 667.76	42 887.76
云南 Yunnan	1.54	12.22	86.24	5 902.82	46 839.26	330 557.91
陕西 Shaanxi	0.10	7.57	92.33	205.60	15 563.92	189 830.49
总计 Total	11.71	15.86	72.43	323 318.24	437 743.45	1 999 017.78

气候变化情景 Climate change scenario	年 Year	年降水量范围 Range of annual precipitation (mm)	年降水量 Annual precipitation (mm)	年平均气温范围 Range of annual mean air temperature (℃)	年平均气温(℃) Annual mean air temperature
当前 Current	1950-2000	16 - 4 107	596.41	-16.2 - 25.1	5.2
A1B气候情景 SRES-A1B	2020-2029	30 - 4 233	591.90	-15.3 - 25.8	6.2
	2050-2059	47 - 4 285	642.52	-14.4 - 26.9	7.2
	2080-2089	46 - 4 337	684.50	-13.3 - 27.8	8.1
A2气候情景 SRES-A2	2020-2029	20 - 4 200	584.86	-15.3 - 26.0	6.2
	2050-2059	46 - 4 239	638.94	-14.4 - 26.6	7.0
	2080-2089	56 - 4 284	666.36	-12.8 - 28.0	8.6
B1气候情景 SRES-B1	2020-2029	41 - 4 213	587.04	-15.2 - 26.0	6.1
	2050-2059	38 - 4 241	614.68	-14.9 - 26.3	6.6
	2080-2089	53 - 4 291	640.00	-14.1 - 26.8	7.2

气候变化下桃儿七潜在地理分布的预测

Predictions of potential geographical distribution of Sinopodophyllum hexandrum under climate change

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气候变化情景 Climate change scenarios	时间 Time	海拔范围 Range of elevation (m)	平均海拔 Average elevation (m)	经度范围 Range of longitude (°)	纬度范围 Range of latitude (°)
当前 Current	1950-2000	1 311-4 530	3 123	90.88-106.83	26.96-38.48
SRES-A1B	2020-2029	1 785-4 270	3 290	92.94-107.25	27.17-38.67
	2050-2059	1 593-5 087	3 500	90.80-106.83	26.87-38.45
	2080-2089	1 982-4 870	3 789	89.67-105.42	27.18-38.34
SRES-A2	2020-2029	1 700-5 281	3 143	92.81-107.52	28.20-38.38
	2050-2059	1 920-5 202	3 421	90.80-104.93	27.11-39.16
	2080-2089	1 570-5 669	4 016	89.67-106.19	27.10-38.42
SRES-B1	2020-2029	1 350-5 225	3 219	90.39-108.60	27.21-38.46
	2050-2059	1 340-4 912	3 347	92.09-107.61	26.28-38.67
	2080-2089	1 667-5 429	3 576	90.80-106.59	24.07-39.03

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