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Abstract
Vegetation phenology does not only serve as a key index of terrestrial ecosystem response to worldwide climate change but also has a major influence on plant productivity and the carbon cycle. In the current research, the change of vegetation phenological parameters was studied and the impact exerted by climate change on phenological phases in northeast China for 1982–2014 was explored using the latest edition of the Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS NDVI3g) dataset. The results showed that the start of the growing season (SOS) slightly advanced, the end of the growing season (EOS) showed a significant delay, and the length of the growing season (LOS) exhibited a significant prolonging at the regional scale. At the different vegetation types scale, there existed diverse responses of vegetation phenological phases to climate change for forest, grassland, and cultivated land. Significant decreasing trends in the SOS occupied 19.1% of the entire research area, whereas pixels with significantly increasing trends in the SOS accounted for 13.1%. The EOS was delayed in most of the study region (approximately 72.1%). As the result of the variations of SOS and EOS, the LOS was obviously enhanced (p < 0.05) in 29.7% of the research area. According to the correlation of vegetation phenology with climate factors, the SOS had a significant negative relationship with the average temperature in springtime, while the EOS was notably negatively connected to summer total precipitation at the regional scale. At the pixel scale, the correlation of phenological parameters with climate variables showed strong spatial heterogeneities. This study contributes to the comprehension of the responses of vegetation phenology to climate change.
Highlights
According to the correlation of vegetation phenology with climate factors, the start of the growing season (SOS) had a significant negative relationship with the average temperature in springtime, while the end of the growing season (EOS) was notably negatively connected to summer total precipitation at the regional scale
The results showed that the SOS slightly advanced, the EOS showed a significant delay, and the length of the growing season (LOS) exhibited a significant prolonging at the regional scale
To identify the spatial distribution pattern for vegetation phenology of northeast China, this study identified the average values of vegetation phenological parameters in 1982–2014 (Figure 3)
Summary
Phenology is crucial for quantifying the variations of vegetation phenological shifts, comprehending how climate change affects terrestrial ecosystems, and assessing the terrestrial vegetation productivity and carbon budget at both the regional and global scales [1,2,3,4,5,6,7,8,9,10].Many previous studies have used traditional field observation approaches to analyse the interannual variability of vegetation phenology and determine the correlation of phenological shifts and climate change at the species scale [1,11]. Phenology is crucial for quantifying the variations of vegetation phenological shifts, comprehending how climate change affects terrestrial ecosystems, and assessing the terrestrial vegetation productivity and carbon budget at both the regional and global scales [1,2,3,4,5,6,7,8,9,10]. Remote sensing is a powerful method of providing data related to large-scale phenological events and has been frequently employed in recent years [6]. Many researchers have employed remote sensing Normalized Difference Vegetation Index (NDVI) data for monitoring vegetation phenology, mainly derived from platforms such as the Advanced Very High. The latest edition of the Global Inventory Modeling and Mapping
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