Abstract
Vegetation phenology is a key biological indicator for monitoring terrestrial ecosystems and global change, and regions with the most obvious phenological changes in vegetation are primarily located at high latitudes and altitudes. Over the past three decades, investigations of obvious phenological changes in vegetation at middle and high latitudes in the Northern Hemisphere have provided significant contributions to understanding global climate change. In this study, phenological parameters were extracted from the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) to analyze the spatial and temporal characteristics of vegetation phenological changes above 40°N in the Northern Hemisphere from 1982–2013. The results showed that the start of season (SOS) was significantly advanced (−2.2 ± 0.6 days·decade−1, p < 0.05) and that the end of season (EOS) was slightly delayed (0.78 ± 0.6 days·decade−1, p = 0.21) over the entire study area in the initial 21 years (1982–2002). When the time scale was extended to 2013, the change rate of the SOS and EOS was significantly reduced; in addition, the SOS was delayed (3.2 ± 1.7 days·decade−1, p < 0.05), and the EOS was advanced (4.5 ± 0.9 days·decade−1, p < 0.05) over the entire study area in the last 11 years (2003–2013). The trends of advanced SOS and delayed EOS over the past three decades were slower than those over the initial two decades on a hemispheric scale. The change trends showed obvious variability with different vegetation types and were greater for woody plants than for herbaceous plants. For broad-leaved forest, the SOS was significantly advanced (2 ± 0.5 days·decade−1, p < 0.05) and the EOS was significantly delayed (2.7 ± 0.6 days·decade−1, p < 0.05) from 1982–2013. The trend of delayed EOS was greater than that of advanced SOS for different vegetation types. With respect to the spatial distribution of phenological trends in the Northern Hemisphere, the trends of advanced SOS and delayed EOS were strongest in Europe followed by North America, and the trends were least significant in Asia. Coniferous forest, shrub forest, grassland, and the entire study area have the same change trends for the two time periods (1982–2002 and 2003–2013), and the increased rate of the phenology parameters has decelerated over the most recent decade. The length of season (LOS) of broad-leaved forest and mixed forest over the past 32 years shows a strong increased trend, and simultaneously, the SOS and EOS show an advanced trend and a delayed trend, respectively
Highlights
Global warming is an undeniable phenomenon [1], and global climate change is a major environmental problem; it has become a focal point for governments, researchers, and the public in different countries
An inversion of phenological parameters is performed using the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g datasets for the period 1982–2013 to analyze the spatial patterns of means, spatial patterns of trends, spatial trends over the entire region, and different vegetation types
The main findings can be summarized as follows: With respect to the spatial distribution of multi-year mean data, the start of season (SOS) was generally delayed from low to high latitudes, and the end of season (EOS) was progressively advanced in the Northern Hemisphere
Summary
Global warming is an undeniable phenomenon [1], and global climate change is a major environmental problem; it has become a focal point for governments, researchers, and the public in different countries. Assessment Report (2007) by the IPCC, the top 14 warmest years have all occurred in the last 12. Ecosystems that are most obviously impacted by global warming are mainly located at high latitudes and altitudes [2,3,4,5,6]. In these regions, vegetation is substantially influenced by cold weather and has a sensitive response to climatic warming. The unique geographical location at high latitudes and altitudes provides a rare opportunity for detecting climate-driven changes in vegetation and serves as an ideal location for monitoring global change. Such work is crucial for understanding the potential impact of climate change on natural ecosystems to maximally reduce the negative impact of climate change and utilize its advantages
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