Analysis of asymmetry in diurnal warming and its impact on vegetation phenology in the Qinghai-Tibetan Plateau using MODIS remote sensing data

Abstract. Because of its high altitude, the Qinghai-Tibetan Plateau (QTP) serves as a de facto ecological barrier between China and Southeast Asia. Studying the phenological characteristics of vegetation on QTP and their response to climate change can help us to understand how climate change can impact on highland terrestrial ecosystems and how to improve predicting highland vegetation phenology. Using long-term NDVI data we derived from the MODIS spectral reflectance product (MOD09A1) and in situ climate data in QTP, we investigated (1) the trends of temporal and spatial variations in the phenological characteristics of the highland vegetation, such as the start of growing season (SOS), middle time of growing season (MOS), end of growing season (EOS), and length of growing season (LEN), and (2) the responses of SOS, MOS, and EOS to asymmetry in diurnal warming, i.e., asymmetry in the preseason daily daytime maximum temperature (Tmax) and daily nighttime minimum temperature (Tmin). Results showed that (1) the vegetation phenology in QTP displayed a salient zonal distribution pattern. From the northwest to the southeast, the vegetation SOS and MOS gradually advanced, EOS decreased, and LEN extended; (2) Tmin warmed up faster than Tmax, which indicated that daytime warming and nighttime warming were asymmetrical; (3) the increase in preseason Tmax and that in preseason Tmin played different roles in SOS, MOS, and EOS; and (4) the preseason Tmin showed a stronger control on vegetation phenology than the preseason Tmax. For instance, a 1°C increase in preseason Tmin advanced SOS by 7.07d (p  <  0.05) and MOS by 6.80d (p  <  0.05), and delayed EOS by 6.70d (p  <  0.05). While a 1°C increase in preseason Tmax delayed the SOS, MOS, and EOS by 5.12d, 4.84d, and 1.04d, respectively.

[1]  Masson-Delmotte,et al.  The Physical Science Basis , 2007 .

[2]  Amanda S. Gallinat,et al.  Changes in autumn senescence in northern hemisphere deciduous trees: a meta-analysis of autumn phenology studies. , 2015, Annals of botany.

[3]  Reinhard Furrer,et al.  Spatial relationship between climatologies and changes in global vegetation activity , 2013, Global change biology.

[4]  Yili Zhang,et al.  Increasing sensitivity of alpine grasslands to climate variability along an elevational gradient on the Qinghai-Tibet Plateau. , 2019, The Science of the total environment.

[5]  Andrew D Richardson,et al.  Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States , 2016, Global change biology.

[6]  Jing M. Chen,et al.  Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn , 2013 .

[7]  P. Beck,et al.  Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI , 2006 .

[8]  S. Piao,et al.  Variations in Vegetation Net Primary Production in the Qinghai-Xizang Plateau, China, from 1982 to 1999 , 2006 .

[9]  W. Dulaney,et al.  Normalized difference vegetation index measurements from the Advanced Very High Resolution Radiometer , 1991 .

[10]  Bruce C. Forbes,et al.  Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series , 2013 .

[11]  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.

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

[13]  Qing Liu,et al.  Positive effects of night warming on physiology of coniferous trees in late growing season: Leaf and root , 2016 .

[14]  Amanda S. Gallinat,et al.  Autumn, the neglected season in climate change research. , 2015, Trends in ecology & evolution.

[15]  Dong He,et al.  Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China , 2018, Remote. Sens..

[16]  Zhang Yili.  Protection and Construction of the National Ecological Security Shelter Zone on Tibetan Plateau , 2012 .

[17]  Josep Peñuelas,et al.  Phenology Feedbacks on Climate Change , 2009, Science.

[18]  Klaus Fraedrich,et al.  Variability of temperature in the Tibetan Plateau based on homogenized surface stations and reanalysis data , 2013 .

[19]  C. Körner,et al.  The interaction between freezing tolerance and phenology in temperate deciduous trees , 2014, Front. Plant Sci..

[20]  Shilong Piao,et al.  Variation in leaf flushing date influences autumnal senescence and next year’s flushing date in two temperate tree species , 2014, Proceedings of the National Academy of Sciences.

[21]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[22]  P. Pandey,et al.  Shared and unique responses of plants to multiple individual stresses and stress combinations: physiological and molecular mechanisms , 2015, Front. Plant Sci..

[23]  Tao Yuan,et al.  The Effect of Snow Depth on Spring Wildfires on the Hulunbuir from 2001-2018 Based on MODIS , 2019, Remote. Sens..

[24]  R. Rawal,et al.  Phenology of high-altitude plants of Kumaun in Central Himalaya, India , 1990 .

[25]  J. Bascompte,et al.  Global change and species interactions in terrestrial ecosystems. , 2008, Ecology letters.

[26]  C. Tucker,et al.  Climate-Driven Increases in Global Terrestrial Net Primary Production from 1982 to 1999 , 2003, Science.

[27]  X. Kuang,et al.  Review on climate change on the Tibetan Plateau during the last half century , 2016 .

[28]  Per Jönsson,et al.  Performance of Smoothing Methods for Reconstructing NDVI Time-Series and Estimating Vegetation Phenology from MODIS Data , 2017, Remote. Sens..

[29]  Liu Yunfeng,et al.  Climatic change on the Tibetan Plateau: Potential Evapotranspiration Trends from 1961–2000 , 2006 .

[30]  Mingjun Ding,et al.  Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009 , 2013 .

[31]  Lin Jiang,et al.  Nighttime warming enhances drought resistance of plant communities in a temperate steppe , 2016, Scientific Reports.

[32]  D. Zhou,et al.  Impact of Climate Change on Temperate and Alpine Grasslands in China during 1982–2006 , 2015 .

[33]  Ming Jiang,et al.  Asymmetric effects of daytime and nighttime warming on spring phenology in the temperate grasslands of China , 2018, Agricultural and Forest Meteorology.

[34]  P. Ciais,et al.  Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation , 2013, Nature.

[35]  Andrew D Richardson,et al.  The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models , 2015, Global change biology.

[36]  P. Ciais,et al.  Terrestrial carbon cycle affected by non-uniform climate warming , 2014 .

[37]  John A. Silander,et al.  Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts , 2015, Proceedings of the National Academy of Sciences.

[38]  Kees van Oers,et al.  Phenology, seasonal timing and circannual rhythms: towards a unified framework , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[39]  Mark D. Schwartz,et al.  Phenology and climate: the timing of life cycle events as indicators of climatic variability and change , 2002 .

[40]  Jianyang Xia,et al.  Photosynthetic overcompensation under nocturnal warming enhances grassland carbon sequestration. , 2009, Ecology.

[41]  Z. Yin,et al.  August temperature variability in the southeastern Tibetan Plateau since AD 1385 inferred from tree rings , 2011 .

[42]  Zhi-Yong Yin,et al.  Temporal trends and variability of daily maximum and minimum, extreme temperature events, and growing season length over the eastern and central Tibetan Plateau during 1961-2003 , 2006 .

[43]  P. Ciais,et al.  Leaf onset in the northern hemisphere triggered by daytime temperature , 2015, Nature Communications.

[44]  Tilden Meyers,et al.  The 2007 Eastern US Spring Freeze: Increased Cold Damage in a Warming World , 2008 .

[45]  Xiaodong Zhang,et al.  A comprehensive analysis of phenological changes in forest vegetation of the Funiu Mountains, China , 2019, Journal of Geographical Sciences.

[46]  Nan Li,et al.  Comparison of Remote Sensing Time-Series Smoothing Methods for Grassland Spring Phenology Extraction on the Qinghai-Tibetan Plateau , 2020, Remote. Sens..

[47]  Paul J. CaraDonna,et al.  Shifts in flowering phenology reshape a subalpine plant community , 2014, Proceedings of the National Academy of Sciences.

[48]  M. Shen,et al.  Strong impacts of daily minimum temperature on the green‐up date and summer greenness of the Tibetan Plateau , 2016, Global change biology.

[49]  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 .

[50]  D. Lobell.  Changes in diurnal temperature range and national cereal yields , 2007 .

[51]  Chaoyang Wu,et al.  Land surface phenology of China's temperate ecosystems over 1999–2013: Spatial–temporal patterns, interaction effects, covariation with climate and implications for productivity , 2016 .

[52]  Yuan Yuan Fu,et al.  [Spatiotemporal variation of vegetation phenology in the Daxing'an Mountains stratified by eco-geographical regions.] , 2016, Ying yong sheng tai xue bao = The journal of applied ecology.

[53]  H. Alexandersson.  A homogeneity test applied to precipitation data , 1986 .

[54]  J. L. Parra,et al.  Very high resolution interpolated climate surfaces for global land areas , 2005 .

[55]  Hong Jiang,et al.  The impacts of climate change and human activities on biogeochemical cycles on the Qinghai‐Tibetan Plateau , 2013, Global change biology.

[56]  I. Esau,et al.  Diurnal asymmetry to the observed global warming , 2017 .

[57]  Q. Wang,et al.  A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China , 2019, Journal of Mountain Science.

[58]  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 .

[59]  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.

[60]  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 .

[61]  O. Sonnentag,et al.  Climate change, phenology, and phenological control of vegetation feedbacks to the climate system , 2013 .

[62]  Camilo Daleles Rennó,et al.  Window Regression: A Spatial-Temporal Analysis to Estimate Pixels Classified as Low-Quality in MODIS NDVI Time Series , 2014, Remote. Sens..

[63]  D. Legates,et al.  Crop identification using harmonic analysis of time-series AVHRR NDVI data , 2002 .

[64]  Shilong Piao,et al.  Delayed autumn phenology in the Northern Hemisphere is related to change in both climate and spring phenology , 2016, Global change biology.

[65]  C. Jeganathan,et al.  Time-series cloud noise mapping and reduction algorithm for improved vegetation and drought monitoring , 2017 .