<p>Understanding past changes in surface vegetation cover is crucial for clarifying spatiotemporal patterns of vegetation, temperature, and humidity variations across Central Asia. In this study, we developed a tree-ring width index chronology for <i>Juniperus excelsa</i> in the western Alborz Mountains of Iran and examined its correlation with the Normalized Difference Vegetation Index (NDVI). Using this relationship, we reconstructed NDVI variations in this region since 1943. Our results indicate that both the tree-ring width index and NDVI from April to August exhibit strong correlations with precipitation from the previous December to the current May, as well as with the May Palmer Drought Severity Index (PDSI). The tree-ring width index is significantly and positively correlated with NDVI from April to August (<i>R</i><sup>2</sup><sub>adj</sub>= 0.562, F=26.616, <i>p</i>&lt;0.001), confirming its effectiveness in representing NDVI fluctuations during this period. The reconstructed NDVI series reveals more pronounced vegetation cover fluctuations since the 1990s compared to the 1940s–1980s. Notably, periods of low vegetation cover occurred in the late 20th to early 21st century, whereas high vegetation cover was observed in the early 2020s. Since 1943, key periods of relatively low vegetation cover include 1946–1955, 1959–1973, 1986–1989, 1997–2002, and 2008–2015. The notably low vegetation cover from 1997 to 2002 coincides with a severe and persistent drought that has affected Central and South Asia since the 1940s. Our findings suggest that vegetation growth in the study area reflects both local climate variations and broader regional or global climate changes. By extending short-term NDVI records obtained via remote sensing, this study provides a long-term perspective on vegetation dynamics, enhancing our understanding of historical vegetation dynamics in Iran and their response to climate fluctuations.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Tree-ring reconstruction of changes in surface vegetation cover in the western Alborz Mountains since AD 1943

  • Yajun Wang,
  • Shengqian Chen,
  • Haichao Xie,
  • Yanan Su,
  • Shuai Ma,
  • Tingting Xie

摘要

Understanding past changes in surface vegetation cover is crucial for clarifying spatiotemporal patterns of vegetation, temperature, and humidity variations across Central Asia. In this study, we developed a tree-ring width index chronology for Juniperus excelsa in the western Alborz Mountains of Iran and examined its correlation with the Normalized Difference Vegetation Index (NDVI). Using this relationship, we reconstructed NDVI variations in this region since 1943. Our results indicate that both the tree-ring width index and NDVI from April to August exhibit strong correlations with precipitation from the previous December to the current May, as well as with the May Palmer Drought Severity Index (PDSI). The tree-ring width index is significantly and positively correlated with NDVI from April to August (R2adj= 0.562, F=26.616, p<0.001), confirming its effectiveness in representing NDVI fluctuations during this period. The reconstructed NDVI series reveals more pronounced vegetation cover fluctuations since the 1990s compared to the 1940s–1980s. Notably, periods of low vegetation cover occurred in the late 20th to early 21st century, whereas high vegetation cover was observed in the early 2020s. Since 1943, key periods of relatively low vegetation cover include 1946–1955, 1959–1973, 1986–1989, 1997–2002, and 2008–2015. The notably low vegetation cover from 1997 to 2002 coincides with a severe and persistent drought that has affected Central and South Asia since the 1940s. Our findings suggest that vegetation growth in the study area reflects both local climate variations and broader regional or global climate changes. By extending short-term NDVI records obtained via remote sensing, this study provides a long-term perspective on vegetation dynamics, enhancing our understanding of historical vegetation dynamics in Iran and their response to climate fluctuations.