毛乌素沙地植被物候变化及其对气候变化的响应

杨梅焕; 靳小燕; 王涛

doi:10.13961/j.cnki.stbctb.20220316.001

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毛乌素沙地植被物候变化及其对气候变化的响应

试验研究

- 毛乌素沙地植被物候变化及其对气候变化的响应
- Vegetation Phenology Change of Mu Us Sandy Land and Its Response to Climate Change
- 水土保持通报 2022年42卷第2期页码：242-249
- 作者机构：
  
  西安科技大学测绘科学与技术学院,陕西,西安,710054
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“毛乌素沙地东南缘土壤—植被反馈机制与植被演替机制研究”(41501571)
- DOI：10.13961/j.cnki.stbctb.20220316.001
  中图分类号： TP79;Q948.11
- 纸质出版：2022
- 稿件说明：
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杨梅焕, 靳小燕, 王涛. 毛乌素沙地植被物候变化及其对气候变化的响应[J]. 水土保持通报, 2022,42(2):242-249.

Yang Meihuan, Jin Xiaoyan, Wang Tao. Vegetation Phenology Change of Mu Us Sandy Land and Its Response to Climate Change[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 242-249.
杨梅焕, 靳小燕, 王涛. 毛乌素沙地植被物候变化及其对气候变化的响应[J]. 水土保持通报, 2022,42(2):242-249. DOI： 10.13961/j.cnki.stbctb.20220316.001.

Yang Meihuan, Jin Xiaoyan, Wang Tao. Vegetation Phenology Change of Mu Us Sandy Land and Its Response to Climate Change[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 242-249. DOI： 10.13961/j.cnki.stbctb.20220316.001.

摘要

[目的] 分析植被物候时空变化特征及其对气候变化的响应，为区域荒漠化土地治理以及退化生态环境的恢复重建工作提供理论依据。[方法] 以毛乌素沙地为研究区，基于2000—2019年的MODIS NDVI数据，采用双逻辑函数法拟合植被生长曲线，利用动态阈值法提取植被生长开始日期(SOS)、生长季结束日期(EOS)和生长季长度(GSL)3个物候参数，利用Theil-Sen Median和Mann-Kendall方法对物候进行趋势分析，并利用相关性分析及F检验方法研究物候与气候的关系。[结果] ① SOS呈提前趋势，平均提前0.7 d/a，EOS变化趋势不明显，GSL呈延长趋势，平均延长0.65 d/a。②SOS的多年均值主要集中在一年中的第90—140 d，在空间上由东到西逐渐推迟，EOS的多年均值主要集中在第300—330 d，空间上由南向北逐渐提前，GSL多年均值集中在第180—250 d，空间上由东到西逐渐缩短。③植被SOS与春季累计降水量、3—4月降水量呈负相关的区域面积分别为90.81%，83.85%和61.70%，与春季季前平均温度、3—4月平均温度呈负相关的区域面积为58.85%，60.01%和51.95%。植被EOS与秋季季前累计降水量、9月降水量和10月降水量成正相关的区域面积分别为54.99%，63.67%和42.34%，与秋季季前平均温度、9—10月平均温度呈正相关的区域面积分别为54.95%，44.7%和50.5%。[结论] 毛乌素沙地植被SOS总体呈提前趋势，植被EOS变化趋势不明显，植被GSL呈延长趋势。春季季前累计降水量和3月降水量是影响植被SOS提前的主要影响因素，9月降水量是植被EOS提前的主要影响因素。

Abstract

[Objective] The temporal and spatial variation characteristics of vegetation phenology and its response to climate change were analyzed to provide a theoretical basis for regional desertification land control and restoration

and for reconstruction of degraded ecological environment. [Methods] NDVI data for the Mu Us sandy land from 2000 to 2019 were used to determine the temporal and spatial variation characteristics of vegetation phenology and their responses to climate change. The vegetation growth curve was reconstructed using the double logic function method. The vegetation start of season (SOS)

end of season (EOS)

and growing season length (GSL) were extracted using the dynamic threshold method. Phenology trend was determined by Theil-Sen median and the Mann-Kendall methods. The relationship between phenology and climate was studied by correlation analysis and F test. [Results] ① SOS was advanced by 0.7 day/year; EOS change trend was not obvious; and GSL was extended by 0.75 day/year. ② The multi-year mean value of SOS for vegetation was mainly concentrated at day of year (DOY) 90—140 d

and was gradually delayed from east to west. The multi-year mean value of EOS for vegetation was mainly concentrated at DOY 300—330 d

and was gradually advanced from south to north. The multi-year mean value of GSL for vegetation ranged from 180 to 250 d

and was gradually shortened from east to west. ③ The area of SOS in Mu Us sandy land was negatively correlated with cumulative precipitation in spring (90.81%)

precipitation in March (83.85%)

and precipitation in April (61.70%)

and was negatively correlated with average temperature before the spring season (58.85%)

average temperature in March (60.01%)

and average temperature in April (51.95%). The area of EOS was positively correlated with accumulated precipitation before the autumn season (54.99%)

precipitation in September (63.67%)

and precipitation in October (42.34%)

and was positively correlated with average temperature before the autumn season (54.95%)

average temperature in September (44.70%)

and average temperature in October (50.50%). [Conclusion] Over the period during 2000—2019

vegetation SOS was generally advanced

changes to vegetation EOS were not obvious

and vegetation GSL was prolonged. Cumulative precipitation before spring and precipitation in March were the main factors influencing vegetation SOS advance

and precipitation in September was the main factor influencing vegetation EOS advance.

关键词

Keywords

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