Characterizing Spatial Patterns of Phenology in Cropland of China Based on Remotely Sensed Data

This study used time-series of global inventory modeling and mapping studies （GIMMS） normalized difference vegetation index （NDVI） datasets at a spatial resolution of 8 km and 15-d interval to investigate the spatial patterns of cropland phenology in China. A smoothing algorithm based on an asymmetric Gaussian function was first performed on NDVI dataset to minimize the effects of anomalous values caused by atmospheric haze and cloud contamination. Subsequent processing for identifying cropping systems and extracting phenological parameters, the starting date of growing season （SGS） and the ending date of growing season （EGS） was based on the smoothed NVDI time-series data. The results showed that the cropping systems in China became complex as moving from north to south of China. Under these cropping systems, the SGS and EGS for the first growing season varied largely over space, and those regions with multiple cropping systems generally presented a significant advanced SGS and EGS than the regions with single cropping patterns. On the contrary, the phenological events of the second growing season including both the SGS and EGS showed little difference between regions. The spatial patterns of cropping systems and phenology in Chinese cropland were highly related to the geophysical environmental factors. Several anthropogenic factors, such as crop variety, cultivation levels, irrigation, and fertilizers, could profoundly influence crop phenological status. How to discriminate the impacts of biophysical forces and anthropogenic drivers on phenological events of cultivation remains a great challenge for further studies.

Spatial variations in responses of vegetation autumn phenology to climate change on the tibetan Plateau

Aims Information about changes in the start and end of the vegetation growing season(SOS and EOS)is crucial for assessing ecosystem responses to climate change because of the high sensitivity of both to climate and their extensive influence on ecological processes in temperate and cold regions.climatic warming substantially advanced SOS on the tibetan Plateau from 1982 to 2011.However,it is unclear why EOS showed little delay despite increasing tem-perature over this period.Methods We used multiple methods to determine EOS from the satellite-observed normalized-difference vegetation index and investigated the relationships between EOS and its potential drivers on the tibetan Plateau over 1982-2011.Important findings We found a slight but non-significant delay in regionally averaged EOS of 0.7 day decade−1(P=0.18)and a widespread but weak delaying trend across the Plateau over this period.the inter-annual variations in regionally averaged EOS were driven mainly by pre-season temperature(partial R=0.62,P<0.01),and precipitation and insolation showed weak impact on EOS(P>0.10).Pre-season warming delayed EOS mainly in the eastern half and north-western area of the plateau.In the south-west,EOS was significantly and positively related to SOS,suggesting potentially indirect effects of winter weather conditions on the following autumn’s phenology through regulation of spring phenology.EOS was more strongly related with pre-season temperature in colder and wetter areas,reflecting vegetation adaptation to local climate.Interestingly,pre-season temperature had weaker delaying effects on EOS for vegeta-tion with a shorter growing season,for which SOS had a stronger control on inter-annual variations in EOS than for vegetation with a longer growing season.this indicates that shorter-season tibetan Plateau vegetation may have lower plasticity in adjusting the length of its growing season,whenever it begins,and that climate change is more likely to shift the growing season than extend it for that vegetation.