Abstract

Long-term (1982–2013) datasets of climate variables and Normalized Difference Vegetation Index (NDVI) were collected from Climate Research Union (CRU) and GIMMS NDVI3g. By setting the NDVI values below the threshold of 0.2 as 0, NDVI_0.2 was created to eliminate the noise caused by changes of surface albedo during non-growing period. TimeSat was employed to estimate the growing season length (GSL) from the seasonal variation of NDVI. Statistical analyses were conducted to reveal the mechanisms of climate-vegetation interactions in the cold and semi-arid Upper Amur River Basin of Northeast Asia. The results showed that the regional climate change can be summarized as warming and drying. Annual mean air temperature (T) increased at a rate of 0.13 °C per decade. Annual precipitation (P) declined at a rate of 18.22 mm per decade. NDVI had an insignificantly negative trend, whereas, NDVI_0.2 displayed a significantly positive trend (MK test, p < 0.05) over the past three decades. GSL had a significantly positive rate of approximately 2.9 days per decade. Correlation analysis revealed that, NDVI was significantly correlated with amount of P, whereas, GSL was highly correlated with warmth index (WMI), accumulation of monthly T above the threshold of 5°C. Principal regression analysis revealed that the inter-annual variations of NDVI, NDVI_0.2 and GSL were mostly contributed by WMI. Spatially, NDVI in grassland was more sensitive to P, whereas, T was more important in areas of high elevation. GSL in most of the areas displayed high sensitivity to T. This study examined the different roles of climate variables in controlling the vegetation activities. Further studies are needed to reveal the impact of extended GSL on the regional water balance and the water level of regional lakes, providing the habitats for the migratory birds and endangered species.

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