Start Of Vegetation Growing Season Research Articles

Climatic Constraints of Spring Phenology and Its Variability on the Mongolian Plateau From 1982 to 2021

AbstractThe start of vegetation growing season (SOS) plays an important role in the energy cycle between the land and atmosphere. Due to the limited temporal span of a single satellite sensor through time, the continuous variation of the SOS over 40 years has not been adequately quantified. Using the overlapping periods (2001–2015) between the Global Inventory Modeling and Mapping Studies (GIMMS) (1982–2015) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) (2001–2021) data sets, we construct an NDVI data set covering the period 1982–2021 on the Mongolian Plateau and further construct a map of relative climatic constraint on the SOS (divided into “temperature‐constrained,” “precipitation‐constrained,” and “other” regions) for quantifying SOS variability. We show that the constructed NDVI data set has high consistency and continuity with earlier GIMMS NDVI data. Regions with the SOS constrained by temperature account for 55.3% of the plateau and are located in northwestern and northeastern cold areas, while regions with the SOS constrained by precipitation constitute over 34.7% and are located in central and southwestern drier regions. Importantly, the temperature‐constrained SOS has continuously and significantly advanced, with a total advance of 4.8 days over 40 years. In contrast, the precipitation‐constrained SOS reversed from advancing to delaying in 2005. This suggests that differentiating the climatic constraint on the SOS might be a practical treatment for reducing the uncertainties in the SOS trends in previous studies. Interestingly, the precipitation‐constrained SOS does not significantly correlate to both the chilling and forcing temperatures, indicating less dependency of the SOS on chilling, which may not have been well considered previously.

Effects of Spring Phenology on Grassland Growth in Qilian Mountains Across Multiple Spatiotemporal Scales

AbstractInvestigating the differences in grassland growth and its response to advancing spring phenology and climate change across various spatiotemporal scales is crucial for the sustainable development of alpine mountain regions under a warming and wetting climate. This study analyzed the growth dynamics of grassland in the Qilian Mountains from 2000 to 2019 at seasonal and periodic scales. Using partial wavelet coherency and partial correlation analysis, we investigated the influence of temperature, precipitation, and spring phenology on grassland growth. Additionally, we quantified the dominant factors affecting grassland growth in different ecological zones and elevational gradient. The results indicated that the mean normalized difference vegetation index increased at an average rate of 1.1 and 2.8 × 10−3/year for grassland in spring and summer, respectively. Furthermore, the start of vegetation growing season (SOS) has advanced 6.0 days during 2000–2019. The dominant factor for grassland growth shifted from spring temperature to summer precipitation. The importance of SOS ranked second, significantly influencing 29.3% and 25.1% of grassland during spring and summer, respectively. Grasslands situated above 4,000 m above sea level (ASL) were more sensitive to climate change, with SOS exerting the greatest influence within the elevation range of 2,800–4,000 m ASL. Additionally, the phase difference in the time‐frequency scale of partial wavelet coherency revealed a lag effect of approximately 1 month for summer grassland growth to respond to precipitation. These findings can provide a scientific basis for optimizing global vegetation models and predicting the productivity of alpine mountain grasslands.

Variations of Vegetation Phenology Extracted from Remote Sensing Data over the Tibetan Plateau Hinterland during 2000–2014

How vegetation phenology responds to climate change is a key to the understanding of the mechanisms driving historic and future changes in regional terrestrial ecosystem productivity. Based on the 250-m and 8-day moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data for 2000–2014 in the Three-River Source Region (TRSR) of Qinghai Province, China, i.e., the hinterland of the Tibetan Plateau, we extracted relevant vegetation phenological information (e.g., start, end, and length of growing season) and analyzed the changes in the TRSR vegetation in response to climate change. The results reveal that, under the increasingly warm and humid climate, the start of vegetation growing season (SOS) advanced 1.03 day yr−1 while the end of vegetation growing season (EOS) exhibited no significant changes, which led to extended growing season length. It is found that the SOS was greatly affected by the preceding winter precipitation, with progressively enhanced precipitation facilitating an earlier SOS. Moreover, as the variations of SOS and its trend depended strongly on topography, we estimated the elevation break-points for SOS. The lower the elevations were, the earlier the SOS started. In the areas below 3095-m elevation, the SOS delay changed rapidly with increasing elevation; whereas above that, the SOS changes were relatively minor. The SOS trend had three elevation break-points at 2660, 3880, and 5240 m.

Large-scale prerain vegetation green-up across Africa.

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall-driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of prerain flush effects in some parts of Africa. The spatial extent of this prerain green-up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to-date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of prerain green-up over Africa than previously reported, with prerain green-up being the norm rather than the exception. We also show the relative sparsity of postrain green-up, confined largely to the Sudano-Sahel region. While the prerain green-up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling.