Abstract

Chinese pine (Pinus tabulaeformis) is a highly climate-sensitive species. Presently, the Huanglong Mountains are covered by widespread forests dominated by Chinese pine and thus has a great potential for dendrochronological studies. To increase the knowledge of NDVI changes of the Loess Plateau and their potential influences on the environmental changes, the regional tree-ring chronology from the Huanglong Mountains was used to investigate climate/NDVI relationships. Standard dendrochronological methods were applied to a regional tree-ring series of Pinus tabulaeformis from the Huanglong Mountains, the Loess Plateau. The relationships between ring widths and NDVI/climate factors were investigated by the simple and spatial correlation analysis. The results of the correlation analysis indicated that mean temperature has negative influences on tree growth, while the tree-ring widths of Chinese pine reflect the variations of the normalized difference vegetation index (NDVI). Herein the standard tree-ring width series was used to develop June–July NDVI for the Huanglong Mountains during the period AD 1812–2012, and it explained 41.2 % of the total NDVI variance during the period AD 1982–2006. The results of the spatial analysis show that the reconstructed NDVI has strong drought signals for the Huanglong Mountains. Drought events in the NDVI series are compared to the historical records and climate data in the study area, and show common drought events over much of Shaanxi. These drought-caused famines have had strong influences on the people of Shaanxi during the past 201 years. The moving correlation between March–July temperature and the NDVI reconstruction showed that the recent warming is the most important driving force of the drying trend and the resulting in tree growth decline during the last 30 years. Our reconstructed NDVI is significantly correlated with sea surface temperature in the Indian and the western Pacific Oceans. The linkages to the Indian and Pacific Oceans suggest the connection of regional NDVI variations to large-scale ocean–atmosphere–land circulation systems. Our NDVI reconstruction provides the long-term perspective on the vegetation dynamics of the Huanglong Mountains and is used to guide expectations of future forest variations.

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