Spatiotemporal Variability of Land Surface Phenology in China from 2001-2014

Land surface phenology is a highly sensitive and simple indicator of vegetation dynamics and climate change. However, few studies on spatiotemporal distribution patterns and trends in land surface phenology across different climate and vegetation types in China have been conducted since 2000, a period during which China has experienced remarkably strong El Nino events. In addition, even fewer studies have focused on changes of the end of season (EOS) and length of season (LOS) despite their importance. In this study, we used four methods to reconstruct Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) dataset and chose the best smoothing result to estimate land surface phenology. Then, the phenophase trends were analyzed via the Mann-Kendall method. We aimed to assess whether trends in land surface phenology have continued since 2000 in China at both national and regional levels. We also sought to determine whether trends in land surface phenology in subtropical or high altitude areas are the same as those observed in high latitude areas and whether those trends are uniform among different vegetation types. The result indicated that the start of season (SOS) was progressively delayed with increasing latitude and altitude. In contrast, EOS exhibited an opposite trend in its spatial distribution, and LOS showed clear spatial patterns over this region that decreased from south to north and from east to west at a national scale. The trend of SOS was advanced at a national level, while the trend in Southern China and the Tibetan Plateau was opposite to that in Northern China. The transaction zone of the SOS within Northern China and Southern China occurred approximately between 31.4°N and 35.2°N. The trend in EOS and LOS were delayed and extended, respectively, at both national and regional levels except that of LOS in the Tibetan Plateau, which was shortened by delayed SOS onset more than by delayed EOS onset. The absolute magnitude of SOS was decreased after 2000 compared with previous studies, and the phenophase trends are species specific.

[1]  J. Ronald Eastman,et al.  A Contextual Mann‐Kendall Approach for the Assessment of Trend Significance in Image Time Series , 2011, Trans. GIS.

[2]  P. Ciais,et al.  Variations in satellite‐derived phenology in China's temperate vegetation , 2006 .

[3]  Christian Körner,et al.  Phenology Under Global Warming , 2010, Science.

[4]  Steven W. Running,et al.  A regional phenology model for detecting onset of greenness in temperate mixed forests, Korea: an application of MODIS leaf area index , 2003 .

[5]  D. Hollinger,et al.  Use of digital webcam images to track spring green-up in a deciduous broadleaf forest , 2007, Oecologia.

[6]  Yue Shi,et al.  Phenology shift from 1989 to 2008 on the Tibetan Plateau: an analysis with a process-based soil physical model and remote sensing data , 2013, Climatic Change.

[7]  F. Tao,et al.  Impact of warming climate and cultivar change on maize phenology in the last three decades in North China Plain , 2016, Theoretical and Applied Climatology.

[8]  G. Henebry,et al.  Remote Sensing of Land Surface Phenology: A Prospectus , 2013 .

[9]  Liang Liang,et al.  Validating satellite phenology through intensive ground observation and landscape scaling in a mixed seasonal forest , 2011 .

[10]  Zhongxin Chen,et al.  Characterizing Spatial Patterns of Phenology in Cropland of China Based on Remotely Sensed Data , 2010 .

[11]  Howard E. Epstein,et al.  Recent changes in phenology over the northern high latitudes detected from multi-satellite data , 2011 .

[12]  Shuhua Yi,et al.  Increasing contamination might have delayed spring phenology on the Tibetan Plateau , 2011, Proceedings of the National Academy of Sciences.

[13]  J. Schaber,et al.  Responses of spring phenology to climate change , 2004 .

[14]  M. Gocić,et al.  Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia , 2013 .

[15]  XU Wu-cheng The characteristics, causes of formation and climatic impact of the 1997—1998 El Ni(n)o event , 2004 .

[16]  Wenquan Zhu,et al.  Extension of the growing season due to delayed autumn over mid and high latitudes in North America during 1982–2006 , 2012 .

[17]  Hongyan Liu,et al.  Consistent shifts in spring vegetation green‐up date across temperate biomes in China, 1982–2006 , 2013, Global change biology.

[18]  Li Zhang,et al.  Assessing phenological change and climatic control of alpine grasslands in the Tibetan Plateau with MODIS time series , 2014, International Journal of Biometeorology.

[19]  C. Schaaf,et al.  Evaluating the potential of MODIS satellite data to track temporal dynamics of autumn phenology in a temperate mixed forest , 2015 .

[20]  G. Carbone,et al.  A Model to Predict Peach Phenology and Maturity Using Meteorological Variables , 1997 .

[21]  Mark A. Friedl,et al.  Digital repeat photography for phenological research in forest ecosystems , 2012 .

[22]  Huijuan Cui,et al.  Spatiotemporal Variability in Start and End of Growing Season in China Related to Climate Variability , 2016, Remote. Sens..

[23]  Youngwook Kim,et al.  Climatic Controls on Spring Onset of the Tibetan Plateau Grasslands from 1982 to 2008 , 2015, Remote. Sens..

[24]  Paul Brindley,et al.  Temporal changes in greenspace in a highly urbanized region , 2011, Biology Letters.

[25]  Massimo Menenti,et al.  Reconstruction of global MODIS NDVI time series: performance of harmonic analysis of time series (HANTS). , 2015 .

[26]  P. Ciais,et al.  Has the advancing onset of spring vegetation green‐up slowed down or changed abruptly over the last three decades? , 2015 .

[27]  Victor F. Rodriguez-Galiano,et al.  Characterising the Land Surface Phenology of Europe Using Decadal MERIS Data , 2015, Remote. Sens..

[28]  Mingjun Ding,et al.  Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data , 2015, Journal of Geographical Sciences.

[29]  Chenghu Zhou,et al.  Climate-associated changes in spring plant phenology in China , 2012, International Journal of Biometeorology.

[30]  Huadong Guo,et al.  Detecting winter wheat phenology with SPOT-VEGETATION data in the North China Plain , 2014 .

[31]  Miaogen Shen,et al.  Spring phenology was not consistently related to winter warming on the Tibetan Plateau , 2011, Proceedings of the National Academy of Sciences.

[32]  Shilong Piao,et al.  Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai–Tibetan Plateau , 2014 .

[33]  Chun Chen,et al.  Spatial and Temporal Changes in Vegetation Phenology at Middle and High Latitudes of the Northern Hemisphere over the Past Three Decades , 2015, Remote. Sens..

[34]  Dan Tarpley,et al.  Diverse responses of vegetation phenology to a warming climate , 2007 .

[35]  Annette Menzel,et al.  Recent spring phenology shifts in western Central Europe based on multiscale observations , 2014 .

[36]  E. Luedeling,et al.  Differential responses of trees to temperature variation during the chilling and forcing phases , 2013 .

[37]  S. Piao,et al.  Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis , 2012 .

[38]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[39]  K. Kawamura,et al.  MODIS NDVI and vegetation phenology dynamics in the Inner Mongolia grassland , 2015 .

[40]  Peter M. Atkinson,et al.  The use of MERIS Terrestrial Chlorophyll Index to study spatio-temporal variation in vegetation phenology over India , 2010 .

[41]  Bin Tan,et al.  Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982–2010 , 2014, International Journal of Biometeorology.

[42]  Tao Wang,et al.  Changes in satellite‐derived spring vegetation green‐up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis , 2013, Global change biology.

[43]  Yanhong Tang,et al.  Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai-Xizang Plateau , 2011 .

[44]  Alan H. Strahler,et al.  The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research , 1998, IEEE Trans. Geosci. Remote. Sens..

[45]  Peter M. Atkinson,et al.  Characterising the spatial pattern of phenology for the tropical vegetation of India using multi-temporal MERIS chlorophyll data , 2010, Landscape Ecology.

[46]  P. Atkinson,et al.  Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology , 2012 .

[47]  Quansheng Ge,et al.  The spatial pattern of leaf phenology and its response to climate change in China , 2014, International Journal of Biometeorology.

[48]  Xiaoqiu Chen,et al.  Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China , 2005 .

[49]  Quansheng Ge,et al.  Phenological response to climate change in China: a meta‐analysis , 2015, Global change biology.

[50]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[51]  Fabienne Maignan,et al.  Mild winter and spring 2007 over western Europe led to a widespread early vegetation onset , 2008 .

[52]  E. Luedeling,et al.  Responses of spring phenology in temperate zone trees to climate warming: A case study of apricot flowering in China , 2015 .

[53]  Serge Rambal,et al.  Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements , 2013 .

[54]  S. Running,et al.  A continental phenology model for monitoring vegetation responses to interannual climatic variability , 1997 .

[55]  Quansheng Ge,et al.  Temperature sensitivity of plant phenology in temperate and subtropical regions of China from 1850 to 2009 , 2015 .

[56]  Yanhong Tang,et al.  Influences of temperature and precipitation before the growing season on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau , 2011 .

[57]  Bingwen Qiu,et al.  Spatiotemporal variability of vegetation phenology with reference to altitude and climate in the subtropical mountain and hill region, China , 2013 .

[58]  Shilong Piao,et al.  Temperature, precipitation, and insolation effects on autumn vegetation phenology in temperate China , 2016, Global change biology.

[59]  Siam Lawawirojwong,et al.  Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia. , 2016, Environmental research.

[60]  F. Doblas-Reyes,et al.  Retrospective prediction of the global warming slowdown in the past decade , 2013 .

[61]  Chang-Hoi Ho,et al.  Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008 , 2011 .

[62]  Wentao Cai,et al.  Alpine vegetation phenology dynamic over 16years and its covariation with climate in a semi-arid region of China. , 2016, The Science of the total environment.

[63]  Miaogen Shen,et al.  Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010 , 2015, Global change biology.

[64]  Li Bingyuan,et al.  A New Scheme for Climate Regionalization in China , 2010 .