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植物研究 ›› 2022, Vol. 42 ›› Issue (1): 151-160.doi: 10.7525/j.issn.1673-5102.2022.01.016

• 研究报告 • 上一篇    

气候变化对杉木适生区和生态位的影响

唐兴港1, 袁颖丹2, 张金池1()   

  1. 1.南方现代林业协同创新中心,江苏省水土保持与生态修复重点实验室,南京林业大学林学院,南京 210037
    2.扬州大学园艺与植物保护学院,扬州 225009
  • 收稿日期:2020-09-16 出版日期:2022-01-20 发布日期:2021-12-30
  • 通讯作者: 张金池 E-mail:zhangjc8811@gmail.com
  • 作者简介:唐兴港(1997—),男,硕士,主要从事水土保持和林业生态工程的研究。
  • 基金资助:
    江苏省农业科技自主创新资金项目(CX(17)1004);林业公益性行业科研专项(201504406);江苏省高校优势学科建设工程资助项目

Effects of Climate Change on the Suitable Area and Niche of Cunninghamia lanceolata

Xinggang Tang1, Yingdan Yuan2, Jinchi Zhang1()   

  1. 1.Co -innovation Center for the Sustainable Forestry in Southern China,Jiangsu Province Key Laboratory of Soil and Water Conservation and Ecological Restoration,College of Forestry,Nanjing Forestry University,Nanjing 210037
    2.College of Horticulture and Plant Protection,Yangzhou University,Yangzhou 225009
  • Received:2020-09-16 Online:2022-01-20 Published:2021-12-30
  • Contact: Jinchi Zhang E-mail:zhangjc8811@gmail.com
  • About author:Tang Xinggang(1997—),male,master,main research direction are soil and water conservation and forestry ecological engineering.
  • Supported by:
    Jiangsu Agriculture Science and Technology Innovation Fund(CX(17)1004);National Special Fund for Forestry Scienti?c Research in the Public Interest(201504406);Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)

摘要:

杉木(Cunninghamia lanceolata)是我国主要的造林树种之一,具有重要的药用、经济和生态服务功能。在全球变暖趋势持续的背景下,气候成为制约物种生存和发展的重要因素,其中空间分布和生态位变化对生态过程的解释至关重要。基于211个杉木分布点和20个环境变量,利用MaxEnt模型和R语言的ecospat软件包对杉木适生区和生态位的变化进行研究,分析杉木对未来气候持续变暖的响应。结果表明杉木当前潜在适生区219.67万km2,约占国土总面积的22.88%,主要分布在我国800 mm等降水量线以东的地区,年均温、昼夜温差日均值和最干月降雨量是影响杉木分布的最主要环境变量。未来杉木适生区分布将沿着经纬度方向迁移,高度和低度适生区面积均不断减少。主成分分析(PCA)表明杉木气候生态位在不同时段不同代表性浓度路径下发生转移和扩展,气候生态位中心将向年均温和最暖季降雨量移动。生态位重叠指数均呈现不断下降的趋势,且RCP8.5情景下的生态位重叠率下降最为明显。结果表明全球气候变暖会改变物种的空间分布区域,并将对现存的生态系统产生不同程度的影响。杉木与气候变化关系的研究拓展了人们对气候变化与植物物种生态特征的认识,为杉木乃至乔木树种的保护和利用提供了理论依据。

关键词: 杉木, MaxEnt模型, 气候变化, 潜在适生区, 生态位变化

Abstract:

Cunninghamia lanceolata is the main afforestation tree species in China, which has important functions of medicine, economy and ecological service. With the trend of continued global warming, climate has become an important factor restricting the survival and development of species, among which spatial distribution and niche changes are crucial to the interpretation of ecological processes. To analyze the response of C. lanceolata to future climate warming, 211 C. lanceolata distribution points and 20 environmental variables were taken, MaxEnt model and ecospat R software package were used as methods. The results showed that the current potential suitable area of C. lanceolata was 2.196 7 million km2, about 22.88% of the total land area, mainly distributed in the east of 800 mm equivalent precipitation line. Mean annual temperature, diurnal mean temperature difference and driest monthly rainfall were the main environmental factors affecting the distribution of C. lanceolata. The suitable area of C. lanceolata would migrate along the latitude and longitude directions, and the area of highly and moderately suitable habitats continue to decrease. Principal component analysis(PCA) showed that the climatic niches of C. lanceolata shifted and expanded under different representative concentration paths in different periods, and the centers of the climatic niches would move to the average annual temperature and the warmest seasonal rainfall. The niche overlap index would show a trend of continuous decline, and the niche overlap rate of RCP8.5 show the most obvious decline. The results showed that global warming would change the spatial distribution of species, and affect the existing ecosystem to varying degrees. The research on the relationship between C. lanceolata and climate change expanded people’s understanding of climate change and the ecological characteristics of plant species, and provided a theoretical basis for the protection and utilization of C. lanceolata and even arbors species.

Key words: Cunninghamia lanceolata, MaxEnt model, climate change, potential suitable area, niche changes

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