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[1]张亮,魏彦强,王金牛,等.气候变化情景下黑果枸杞的潜在地理分布[J].应用与环境生物学报,2020,26(04):969-978.
 ZHANG Liang,WEI Yanqiang,et al.The potential geographical distribution of Lycium ruthenicum Murr under different climate change scenarios[J].Chinese Journal of Applied & Environmental Biology,2020,26(04):969-978.
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气候变化情景下黑果枸杞的潜在地理分布()
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《应用与环境生物学报》[ISSN:1006-687X/CN:51-1482/Q]

卷:
26卷
期数:
2020年04期
页码:
969-978
栏目:
研究论文
出版日期:
2020-08-25

文章信息/Info

Title:
The potential geographical distribution of Lycium ruthenicum Murr under different climate change scenarios
作者:
张亮魏彦强王金牛周强刘峰贵陈琼刘飞
1青海师范大学地理科学学院 西宁 810008 2中国科学院西北生态环境资源研究院甘肃省遥感重点实验室 兰州 730000 3中国科学院成都生物研究所 成都 610041 4中国科学院西北生态环境资源研究院冰冻圈科学国家重点实验室 兰州 730000
Author(s):
ZHANG Liang1 2 WEI Yanqiang2? WANG Jinniu3 4ZHOU Qiang1 LIU Fenggui1 CHEN Qiong1 & LIU Fei1
1 College of Geography, Qinghai Normal University, Xining 810008, China 2 Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environmental Resources, Chinese Academy of Sciences, Lanzhou 730000, China 3 Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China 4 State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences, Lanzhou 730000, China
关键词:
黑果枸杞潜在地理分布适宜区气候情景MaxEnt模型
Keywords:
Lycium ruthenicum Murr potential geographical distribution suitable area climate scenario MaxEnt model
摘要:
黑果枸杞(Lycium ruthenicum Murr)是一种多年生、多棘刺灌木,具有丰富的药用、经济和生态价值. 基于中国172个黑果枸杞样点和29个环境因子数据,运用MaxEnt模型,模拟预测黑果枸杞在当前、未来(2050s、2070s)RCP2.6、RCP4.5、RCP8.5气候情景下的潜在地理分布,以刀切法(Jacknife)分析影响其分布的主要环境因子,并采用受试者工作特征曲线(ROC)对预测结果进行检验. 结果表明:(1)MaxEnt模型能够较好地模拟预测黑果枸杞在我国的潜在分布范围. 最湿月降水量、最冷季均温、最冷季降水量、表层土壤砾石含量、年均温、月平均日温差等因子是影响黑果枸杞分布的主要因素. (2)黑果枸杞潜在适宜分布区总面积约为111.942 × 104 km2,主要分布在西北干旱地区沙漠—绿洲过渡地带. (3)不同气候情境下,各等级适宜区面积存在明显差异性. RCP2.6情景下2050s、2070s总适宜区增加,RCP4.5情景下2050s增加、2070s减少,RCP8.5情景下2050s、2070s总适宜区减少. (4)空间叠加分析表明,未来黑果枸杞适宜区呈先增长后减少的变化趋势. 2050s黑果枸杞潜在适宜区向东部和东南部扩张,2070s潜在适宜区总体减少,并向北移动. 综上所述,气候变化对黑果枸杞不同等级适宜区产生的影响不同,高适宜区分布范围相对较为稳定,可以适应未来气候变化;未来适宜区潜在分布范围及其空间迁移存在一定规律性,结果可为沙漠化治理和生态环境保护提供参考信息. (图7 表3 参61)
Abstract:
Lycium ruthenicum Murr is a perennial thorny shrub with abundant medicinal, economic, and ecological values. Based on the Maximum Entropy (MaxEnt) model for species distribution that was used in 172 samples with precise latitudinal and longitudinal coordinates as well as 29 environmental variables in China, this study simulated and predicted the current and future potential distribution of Lycium ruthenicum Murr under different Representative Concentration Pathway (RCP2.6, RCP4.5, and RCP8.5) scenarios in 2050 and 2070. The Jacknife method was used to analyze the main environmental factors that could affect the distribution, while the receiver-operating characteristic curve was used to test the predicted results. The MaxEnt predictions were found to be highly reliable and consistent with the reported sample distributions, while the highest monthly precipitation, coldest average season temperature, coldest season precipitation, surface soil gravel content, average annual temperature, and average daily temperature differences constituted the main environmental factors affecting Lycium ruthenicum Murr distribution. Hence, the most suitable growth area for Lycium ruthenicum Murr (111.942 × 104 km2) is mainly distributed in the arid regions of the northwestern desert and oasis transition zone. Despite the clear differences in the areas of each suitable habitat under different climate scenarios, the total suitable habitat in the 2050s and 2070s increased and decreased under the RCP2.6 and RCP8.5 scenarios, respectively as well as increased and decreased in the 2050s and 2070s under the RCP4.5 scenario, respectively. The spatial overlay analysis demonstrated the increasing and decreasing trend in the suitable habitat of Lycium ruthenicum Murr, where the potential habitat areas for Lycium ruthenicum Murr will expand east and southeast in the 2050s, and then decrease and move northward in the 2070s. In summary, this study examined the different effects of climate change across different grades of suitable habitats, in which the distribution range of highly suitable habitats was relatively stable and can be adapted to future climate changes. The potential distribution range and spatial migration of future suitable habitats showed regularity, providing insights to desertification prevention and ecological and environmental protection.

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更新日期/Last Update: 2020-08-25