Spatial-Temporal Variation Characteristics and Climate Driving Force Analysis of Longbao Alpine Wetland in Recent 32 Years

  • Feifei SHI ,
  • Bingrong ZHOU ,
  • Liangdong YAN ,
  • Donglin QI ,
  • Bin QIAO ,
  • Mingming SHI ,
  • Qi CHEN
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  • Institute of Qinghai Meteorological Science Research,Key Laboratory of Disaster Prevention and Mitigation of Qinghai Province,Xining 810001,Qinghai,China

Received date: 2019-12-16

  Online published: 2020-12-28

Abstract

Wetland is a unique ecosystem formed by the interaction between water and land, which is extremely easy to be affected by the climate change.Taking Longbao, a typical wetland in source region of the Yangtze River, as the target domain, the study applied the random forests method to extract information about the surface type of Longbao from 1986 to 2017 and also analyzed the characteristics of spatial-temporal variations of it.Meanwhile, from a climate perspective, methods such as principal component analysis were employed to quantitatively identify the major climate drivers affecting the wetland evolution.At last, the study built a model for the response relation between the wetland area and the climate change, which could be utilized to predict the evolvement rule of wetland in the future.The following results are summarized: (1) In the past 32 years, there was a spatial nonuniformity in the features of Longbao wetland evolvement because of the long-term influence of terrain; there was a general downtrend in the time dimension, but a change from increasing to decreasing was presented near 2002.Wetland was usually in a steady succession with the Alpine meadow; (2) In the past 32 years, temperature, wind speed and evaporation of Longbao region was in a significant uptrend, while the increase of precipitation is not significant.That would certainly decrease the relative humidity and shorten the days with snow cover.Surface temperature was in a dramatic uptrend, therefore the maximum depth of frozen soil in this region was gradually becoming shallower year by year.In late 2002, an obvious warming and drying trend appeared in the Longbao region; (3) The evolution of the Longbao wetland area has a high response relationship with wind speed, temperature, surface temperature and relative humidity, respectively.

Cite this article

Feifei SHI , Bingrong ZHOU , Liangdong YAN , Donglin QI , Bin QIAO , Mingming SHI , Qi CHEN . Spatial-Temporal Variation Characteristics and Climate Driving Force Analysis of Longbao Alpine Wetland in Recent 32 Years[J]. Plateau Meteorology, 2020 , 39(6) : 1282 -1294 . DOI: 10.7522/j.issn.1000-0534.2019.00139

References

[1]Buckley R, 2011.The economics of ecosystems and biodiversity: Ecological and economic foundations[J].Austral Ecology, 36(6): 34-35.
[2]McGuire A D, Sturm M, Chapin F S, 2003.Arctic Transitions in the Land-Atmosphere System (ATLAS): Background, objectives, results, and future directions[J].Journal of Geophysical Research, 108(D2): 8166-8176.DOI: 10.1029/2002JD002367.
[3]Wu H, Soh L K, Samal A, et al, 2008.Trend analysis of streamflow drought events in Nebraska[J].Water Resources Management, 22 (2): 145-164.DOI: 10.1007/s11269-006-9148-6.
[4]常国刚, 李凤霞, 李林, 2005.气候变化对青海生态与环境的影响及对策[J].气候变化研究进展, 1(4): 172-175.DOI: 10. 3969/j.issn.1673-1719.2005.04.007.
[5]陈桂琛, 黄志伟, 卢学锋, 等, 2002.青海高原湿地特征及其保护[J].冰川冻土, 24(3): 254-259.
[6]青海省气象科学研究所, 青海省湿地保护中心, 青海省卫星遥感中心, 等, 2019.高寒湿地遥感分类技术指南(DB63/T 1746-2019)[S].西宁: 青海省市场监督管理局.
[7]杜际增, 王根绪, 杨燕, 等, 2015.长江黄河源区湿地分布的时空变化及成因[J].生态学报, 35(18): 6173-6182.DOI: 10.5846/stxb201401260196.
[8]谷晓天, 高小红, 马慧娟, 等, 2019.复杂地形区土地利用/土地覆被分类机器学习方法比较研究[J].遥感技术与应用, 34(1): 57-67.DOI: 10.11873/j.issn.1004-0323.2019.1.0057.
[9]何方杰, 韩辉邦, 马学谦, 等, 2019.隆宝滩沼泽湿地不同区域的甲烷通量特征及影响因素[J].生态环境学报, 28(4): 803-811.
[10]侯明行, 刘红玉, 张华兵, 等, 2013.地形因子对盐城滨海湿地景观分布与演变的影响[J].生态学报, 33(12): 3765-3773.DOI: 10.5846/stxb201211121591.
[11]姜琪, 罗斯琼, 文小航, 等, 2020.1961-2014年青藏高原积雪时空特征及其影响因子[J].高原气象, 39(1): 24-36.DOI: 10. 7522/j.issn.1000-0534.2019.00022.
[12]李凤霞, 伏洋, 肖建设, 等, 2011.长江源头湿地消长对气候变化的响应[J].地理科学进展, 30(1): 49-56.
[13]李军, 王京丽, 屈坤, 2020.相对湿度和PM_(2.5)浓度对乌鲁木齐市冬季能见度的影响[J]. 中国环境科学, 40(8):3322-3331. DOI:10.19674/j.cnki.issn1000-6923.2020.0371.
[14]李林, 吴素霞, 朱西德, 2008.21世纪以来黄河源区高原湖泊群对气候变化的响应[J].自然资源学报, 23(2): 245-253.DOI: 10.3321/j.issn: 1000-3037.2008.02.009.
[15]栗云召, 于君宝, 韩广轩, 等, 2011.黄河三角洲自然湿地动态演变及其驱动因子[J].生态学杂志, 30(7): 1535-1541.
[16]罗磊, 2005.青藏高原湿地退化的气候背景分析[J].湿地科学, 3(3): 190-199.DOI: 10.3969/j.issn.1672-5948.2005.03.005.
[17]马转转, 张明军, 王圣杰, 等, 2019.1960-2015 年青藏高寒区与西北干旱区升温特征及差异[J].高原气象, 38(1): 42-54.DOI: 10.7522/j.issn.1000-0534.2018.00074.
[18]祁栋林, 肖宏斌, 李晓东, 等, 2016.1964-2013年青海省不同生态功能区蒸发皿蒸发量的变化特征[J].干旱气象, 34(2):234-242.DOI: 10.11755/j.issn.1006-7639.2016.02.0234.
[19]宋长春, 2003.湿地生态系统对气候变化的响应[J].湿地科学, 1(2): 122-127.DOI: 10.13248/j.cnki.wetlandsci.2003.02.008.
[20]孙广友, 金会军, 于少鹏, 2008.沼泽湿地与多年冻土的共生模式—以中国大兴安岭和小兴安岭为例[J].湿地科学, 6(4): 479-485.DOI: 10.13248/j.cnki.wetlandsci.2008.04.009.
[21]王根绪, 李元寿, 王一博, 等, 2007.近40年来青藏高原典型高寒湿地系统的动态变化[J].地理学报, 62(5): 481-491.DOI: 10.3321/j.issn: 0375-5444.2007.05.004.
[22]韦玮, 李增元, 谭炳香, 等, 2011.基于多角度高光谱CHRIS影像的隆宝滩湿地遥感分类方法研究[J].林业科学研究, 24(2): 159-164.
[23]魏凤英, 2007.现代气候统计诊断与预测技术[M].北京: 气象出版社, 99-104.
[24]许建伟, 高艳红, 彭保发, 等, 2020.1979-2016年青藏高原降水的变化特征及成因分析[J].高原气象, 39(2): 234-244.DOI: 10.7522/j.issn.1000-0534.2019.00029.
[25]徐丽娇, 胡泽勇, 赵亚楠, 等, 2019.1961-2010年青藏高原气候变化特征分析[J].高原气象, 38(5): 911-919.DOI: 10.7522/j.issn.1000-0534.2018.00137.
[26]杨爱民, 朱磊, 陈署晃, 等, 2019.1975—2015年玛纳斯河流域土地利用变化的地学信息图谱分析[J].应用生态学报, 30(11): 3863-3874.DOI: 10.13287/j.1001-9332.201911.017.
[27]燕云鹏, 徐辉, 邢宇, 2015.1975—2007年间三江源不同源区湿地变化特点及对气候变化的响应[J].测绘通报 (增刊): 5-10.
[28]赵峰, 刘华, 张怀清, 等, 2012.近30年来三江源典型区湿地变化驱动力分析[J].湿地科学与管理, 8(3): 57-60.DOI: 10. 3969/j.issn.1673-3290.2012.03.16.
[29]赵全宁, 严应存, 刘彩红, 等, 2018.1980—2017年青海省玉树地区季节冻土变化对气候变暖的响应[J].冰川冻土, 40(5): 899-906.DOI: 10.7522/j.issn.1000-0240.2018.0097.
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