Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Abstract

Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Response of Vegetation Photosynthetic Phenology to Urbanization in Dongting Lake Basin, China

“…Specifically, the SOS or EOS dates were defined as the first day of the year in the rising or falling phase when the SIF ratio reaches 0.5 in this study. The threshold of 0.5 has been proved to be very effective for determining the vegetation phenology, which has been verified by multiple studies based on ground observation data from the subtropical region of China [10,24,42].…”

“…The regional vegetation classification data for the Dongting Lake basin were derived from the rasterization of a digitized 1:1,000,000 vegetation map of China [38]. To analyze the sensitivity of different vegetation to urbanization, we selected four main vegetation types in the subtropical region of China, including evergreen coniferous forest (ECF), evergreen broadleaved forest (EBF), shrub, and grassland [24]. In addition, because of the impacts of sparse vegetation on the extraction of vegetation phenology [39], we used Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data to identify the areas with low vegetation cover.…”

“…As compared with the fixed threshold method, the dynamic threshold method can dynamically set the threshold value according to different conditions, thereby eliminating the effect of background values and better reflecting the growth stage of the same vegetation cover under different spatial and temporal conditions [39]. Several studies have verified that the dynamic threshold method has considerable accuracy for vegetation phenology extraction in China [24,42]. The formula is as follows:…”

“…Although vegetation phenology in mid-to-high latitude regions are well studied [23], subtropical regions remain poorly studied, resulting in a very limited understanding of the response of subtropical vegetation phenology to urbanization. This represents an important gap in current knowledge because subtropical regions are characterized by diverse vegetation types with high biodiversity, which play a key role in the global carbon cycle and climate change [24]. In addition, studies on the factors influencing vegetation tend to analyze its relationship with natural factors, whereas the impact of human activities is rarely quantified.…”

“…Recently, the remote sensing of solar-induced chlorophyll fluorescence (SIF) has provided a new perspective on the detection of vegetation phenology [28][29][30]. Because chlorophyll fluorescence can reflect the photosynthetic information of vegetation, the use of SIF for inverting vegetation physiological change in subtropical regions is more reliable than the use of vegetation indices [24,31], enabling more accurate monitoring of the photosynthetic phenology of subtropical vegetation.…”