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准噶尔盆地植被与土壤盐渍化关联性变化趋势分析
引用本文:杜秉晨曦,程勇翔,吴玲.准噶尔盆地植被与土壤盐渍化关联性变化趋势分析[J].生态学报,2021,41(23):9364-9376.
作者姓名:杜秉晨曦  程勇翔  吴玲
作者单位:石河子大学, 生命科学学院, 石河子 832000
基金项目:欧盟Erasmus+项目(598838-EPP-1-2018-EL-EPPKA2-CBHE-JP)
摘    要:准噶尔盆地作为北疆地区主要的气候单元其环境变化会影响北疆地区整体的的生态环境变化。植被作为衡量区域生态环境的重要指标直接反映了准噶尔盆地的生态状况,近年来受到全球气候变化的影响准噶尔盆地地区气候格局发生改变,盆地相比于往年降水和气温明显升高,这种改变影响了盆地的植被变化同时也会在部分地区诱发土壤盐渍化灾害。土壤盐渍化是我国西北地区常见的导致植被退化的因素,其生成原因与地形和气候因素有关。为了探究准噶尔盆地植被变化与土壤盐渍化的关联性,基于2002-2019年生长季MOD09A1遥感影像数据,利用最大值合成法、Mann-Kendall趋势分析,Hurst趋势分析法、相关性分析等方法对准噶尔盆地植被和土壤盐渍化变化趋势以及两者的关联性进行了分析。结果表明,受区域降水和气温升高的影响,近20年来准噶尔盆地生长季植被整体呈增加趋势,各季节增加区域面积占比为63.50%-90.93%,平均为77.98%。土壤盐渍化呈减少趋势,各季减少区域面积占比为46.50%-86.78%,平均为70.68%。在地形低洼、排水不畅的区域土壤盐渍化程度加重,植被因盐分胁迫导致衰退,植被减少及巨大的蒸发降水比使得该地区土壤进一步变干,湿度降低。关联性分析结果表明各季植被与土壤盐渍化的变化中呈显著负相关的区域面积占比为37.36%-57.83%,平均为51.75%。Hurst趋势预测结果表明,当前植被和土壤盐渍化两者呈显著性变化的区域未来预测与当前变化方向相同,两者呈一般性变化的区域未来预测与当前相反。研究有助于在全球气候变化背景下了解准噶尔盆地近年来生态环境变化,结果为区域生态环境的可持续发展提供参考。

关 键 词:植被  土壤盐渍化  变化趋势  相关性分析
收稿时间:2020/9/24 0:00:00
修稿时间:2021/6/10 0:00:00

Analysis of negative correlation between vegetation and soil salinization in Junggar Basin
DU Bingchenxi,CHENG Yongxiang,WU Ling.Analysis of negative correlation between vegetation and soil salinization in Junggar Basin[J].Acta Ecologica Sinica,2021,41(23):9364-9376.
Authors:DU Bingchenxi  CHENG Yongxiang  WU Ling
Institution:College of Life Science, Shihezi University, Shihezi 832000, China
Abstract:As the main climate unit in Northern Xinjiang, the environmental change of Junggar basin will affect the overall ecological environment change of Northern Xinjiang. Vegetation, as an important indicator of regional ecological environment, which directly reflects the ecological situation of Junggar basin. In recent years, under the influence of global climate change, the climate pattern of Junggar basin has changed. Compared with previous years, the precipitation and temperature in the basin have increased significantly. This change affects the vegetation change in the basin, and also induces soil salinization in some areas. Soil salinization is a common factor leading to vegetation degradation in Northwest China, which is related to terrain and climate factors. In order to explore the relationship between vegetation change and soil salinization in Junggar basin, this study was based on MOD09A1 remote sensing image data during the growing season from 2002 to 2019, this study analyzed the variation trend of plant cover and soil salinization in Junggar Basin and the correlation between them by using of the methods of maximum value composite, Mann-Kendall trend analysis, Hurst trend analysis and correlation analysis. The results showed that in the last 20 years, the plant cover in Junggar Basin was increasing in the growing season due to the influence of the regional precipitation and climate warming. The proportion of the increased area in each season was 63.50%-90.93%, with an average of 77.98%. Soil salinization, however, showed a decreasing trend, with a decreased area of 46.50%-86.78% in each season and the average value was 70.68%. In the low-lying area with poor drainage, the degree of soil salinization increased, the vegetation declined due to salt stress, the decrease of vegetation and the huge ratio of evaporation and precipitation made the soil further dry and the humidity decreased. The correlation analysis indicated that the proportion of areas with significantly negative correlation between vegetation and soil salinization in each season were 37.36%-57.83%, with an average of 51.75%. And the results of Hurst trend prediction suggested that the future prediction direction of areas with significant change in aspects above are the same as the current change trend, while one with a general change is opposite to the current change direction in future direction. This study devoted to obtain the information of the ecological environment changes in Junggar Basin in recent years under the global climate change background, in order to provide references for the sustainable development of regional ecological environment.
Keywords:vegetation  soil salinization  trend change  correlation analysis
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