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藏北高山嵩草草甸群落特征及生产力对模拟增温幅度的响应
引用本文:李军祥,张扬建,朱军涛,曾辉,常文静,丛楠,刘瑶杰,俎佳星,黄珂,朱艺旋,王荔,唐泽,陈宁.藏北高山嵩草草甸群落特征及生产力对模拟增温幅度的响应[J].生态学报,2019,39(2):474-485.
作者姓名:李军祥  张扬建  朱军涛  曾辉  常文静  丛楠  刘瑶杰  俎佳星  黄珂  朱艺旋  王荔  唐泽  陈宁
作者单位:北京大学深圳研究生院;深圳;深圳;华中农业大学资源与环境学...;西南民族大学生命科学与技...;青海大学农牧学院;青海大...;兰州大学草地农业科技学院...;北京大学深圳研究生院;甘肃农业大学;青海大学;;高原生态研究所;西藏大学...;青海大学农牧学院;;青海省工程咨询中心;中国...
基金项目:深圳;华中农业大学资源与环境学...;西南民族大学生命科学与技...;青海大学农牧学院;青海大...;兰州大学草地农业科技学院...;北京大学深圳研究生院;甘肃农业大学;青海大学;;高原生态研究所;西藏大学...;青海大学农牧学院;;青海省工程咨询中心;中国...
摘    要:青藏高原气候严酷,陆地表层生态系统脆弱,其高寒植物群落特征及生态系统生产力对气候变化的响应极其敏感。利用开顶箱(OTCs,Open Top Chambers)式装置在藏北高山嵩草(Kobresia pygmaea)草甸设置不同增温梯度实验(W1、W2、W3、W4),探究增温对高寒草甸植物群落特征及地上生产力的影响。研究结果表明:1)与对照样地相比,增温减少了植物群落总盖度(2015年,W1、W2、W3、W4分别显著减少了28%、23%、59%、60%; 2016年,W4显著减少了83%)和高山嵩草盖度(2015年,W1、W2、W3、W4分别显著减少了26%、33%、681%、64%; 2016年,W4显著减少了85%),而低幅度增温(W1、W2)对委陵菜属植物盖度无显著影响,高幅度增温(W3、W4)显著减少了委陵菜属植物盖度(2015年,W3、W4分别显著减少了58%和60%;2016年,W4显著减少了71%); 2)对整个植物群落而言,增温幅度较低时,增温对群落的生长和生物量的积累有促进作用,当温度升高超过一定程度,这种促进作用会逐渐减弱甚至变成抑制作用(2015年,W4显著减少了地上生物量69%; 2016年,W4显著减少了地上生物量82%); 3)高山嵩草盖度和其他物种总盖度存在显著的年际差异,而委陵菜属植物盖度无明显的年际变化。研究结果预示着,一定程度的升温会促进高寒草甸植物群落的生长,但温度升高超过一定幅度时,会导致草地生产力下降,草地退化加剧,同时当地群落中委陵菜属植物在全球变化背景下相对稳定,这类物种在未来气候变暖的背景下可能具有更强的竞争力。

关 键 词:地上生产力  群落特征  多梯度增温  高山嵩草草甸  藏北高原
收稿时间:2017/11/28 0:00:00
修稿时间:2018/8/23 0:00:00

Responses of community characteristics and productivity to a warming gradient in a Kobresia pygmaea meadow of Tibetan Plateau
LI Junxiang,ZHANG Yangjian,ZHU Juntao,ZENG Hui,CHANG Wenjing,CONG Nan,LIU Yaojie,ZU Jiaxing,HUANG Ke,ZHU Yixuan,WANG Li,TANG Ze and CHEN Ning.Responses of community characteristics and productivity to a warming gradient in a Kobresia pygmaea meadow of Tibetan Plateau[J].Acta Ecologica Sinica,2019,39(2):474-485.
Authors:LI Junxiang  ZHANG Yangjian  ZHU Juntao  ZENG Hui  CHANG Wenjing  CONG Nan  LIU Yaojie  ZU Jiaxing  HUANG Ke  ZHU Yixuan  WANG Li  TANG Ze and CHEN Ning
Institution:Peking University Shenzhen Graduate School, Shenzhen 518055, China;Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China;College of Resources and Environmental, University of Chinese Academy of Sciences, Beijing 100190, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,Peking University Shenzhen Graduate School, Shenzhen 518055, China;College of Urban and Environmental Sciences, Peking University, Beijing 100871, China,Peking University Shenzhen Graduate School, Shenzhen 518055, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100190, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100190, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100190, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100190, China,Peking University Shenzhen Graduate School, Shenzhen 518055, China;Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100190, China and Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100190, China
Abstract:The community characteristics and productivity of alpine ecosystems are extremely sensitive to climate change in Qinghai-Tibet Plateau owing to harsh climatic environments. To explore the effects of warming on ecosystem productivity and their inter-annual differences in an alpine meadow, field experiments with temperature-gradient treatments (W1, W2, W3, and W4) using open top chambers (OTCs) were conducted in Tibetan Plateau. The results showed that the warming effect decreased the total coverage of the plant community (W1, W2, W3, and W4 significantly reduced plant community coverage by 28%, 23%, 59%, and 60% in 2015(P < 0.05), respectively; W4 significantly reduced plant community coverage by 83% in 2016(P < 0.05)) and the coverage of Kobresia pygmaea (W1, W2, W3, and W4 significantly reduced the coverage of K. pygmaea by 26%, 33%, 61%, and 64% in 2015(P < 0.05), respectively; W4 significantly reduced the coverage of K. pygmaea by 85% in 2016(P < 0.05)) compared with control treatment. The lower warming treatments (W1 and W2) had no significant effects on the coverage of Potentilla, whereas the higher warming treatments (W3 and W4) significantly reduced the coverage of Potentilla (W3, W4 significantly reduced the coverage of Potentilla by 58% and 60% in 2015(P < 0.05), respectively; W4 significantly reduced the coverage of Potentilla by 71% in 2016(P < 0.05). The warming treatments with a lower temperature range promoted growth and biomass accumulation of the community, whereas weakened the promotion effects or even inhibited growth and biomass accumulation when the temperature increased above a certain degree (W4 significantly reduced the aboveground biomass by 69% in 2015(P < 0.05); W4 significantly reduced the aboveground biomass by 82% in 2016(P < 0.05)). There were significant differences in the coverage of K. pygmaea and other species in the growth season between 2015 and 2016, but no significant changes were observed for Potentilla coverage. This study indicated that moderate warming is conducive for plant growth, but excessive warming can lead to declined grassland productivity and the deterioration of alpine meadows. Furthermore, Potentilla species from local communities are more resistant to global change, indicating their strong competitiveness in facing future climate warming.
Keywords:aboveground productivity  community characteristics  gradient warming  Kobresia pygmaea alpine meadow  Tibetan Plateau
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