Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012

Ding, M. D.; Li, Lan-hui; Nie, Yong; Chen, Qian; Zhang, Yili

doi:10.1007/s11629-015-3600-0

Cited by 25 publications

(18 citation statements)

References 57 publications

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“…The advancement of SG is about 10.4 days decade −1 from 2001 to 2012 in Tibetan Plateau, based on combined AVHRR NDVI over 1982-2000and SPOT-VGT NDVI over 2001(Zhang et al 2013. However, this magnitude of SG shift is very different from the SG trend over 2000-2011 inferred from single AVHRR NDVI, which inferred insignificant SG trend in the Tibetan Plateau (Ding et al 2016).…”

Section: Introductionmentioning

confidence: 81%

Heterogeneous spring phenology shifts affected by climate: supportive evidence from two remotely sensed vegetation indices

Riley

Koven

et al. 2019

Environ. Res. Commun.

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The Northern Hemisphere spring greenup (SG) has advanced between 0-12 days per decade since early 1980s as inferred from multiple satellite time series. The wide range of SG shifts is mainly due to the fact that these studies cover different periods and regions, and using different satellite records. Assessing the spatial heterogeneity of SG trends associated with different satellites is essential for robustly interpreting phenological dynamics and their responses to climate. We investigated the heterogeneity of the SG trends and their responses to climate variability with two satellite products (1) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and (2) Advanced Very High Resolution Radiometer (AVHRR) over the period 2001-2013. Both MODIS and AVHRR agreed in showing the spatial distribution of mean SG, and SG advancement in northern Canada, the eastern United States, and Russia, and SG delay in western North America, parts of Baltic Europe, and East Asia. However, we identified contrasting MODIS and AVHRR SG trends in the northern high latitudes. Our analyses of correlations between SG and preseason climate drivers indicated that temperature dominated the interannual variability of SG. Preseason, the period preceding SG and highly correlated with the timing of SG has experienced much stronger warming than the spring season. MODIS and AVHRR indicated consistent temperature sensitivity of SG across biomes, even though the MODIS inferred SG is better correlated and more sensitive to temperature across biomes as compared to AVHRR. The sensitivities of SG to temperature across biomes is stable but with a slight increase over 2001-2013, in comparison with that over 1988-2000. The increased SG-temperature sensitivity is associated with increased precipitation during the spring season, which regulated the sensitivity of SG to spring temperature.

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Section: Introductionmentioning

confidence: 81%

Heterogeneous spring phenology shifts affected by climate: supportive evidence from two remotely sensed vegetation indices

Riley

Koven

et al. 2019

Environ. Res. Commun.

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“…Yu et al () reported that the SOS of the Tibetan Plateau derived from the GIMMS NDVI data set using the polynomial fitting and NDVI threshold method advanced from 1982 to the mid‐1990s and retreated after the mid‐1990s because of the increasing winter temperature and spring temperature. By contrast, some other studies reported that no significant SOS trend was found from 1982 to 2013 (Ding et al, ; Liu et al, ). Ding et al () used the polynomial method and the GIMMS3g (version 0) and SPOT‐VEG data, while Liu et al () used the logistic method (logistic fitting and NDVI inflection detecting) and the advanced very high resolution radiometer (AVHRR) and MODIS data.…”

Section: Introductionmentioning

confidence: 84%

“…By contrast, some other studies reported that no significant SOS trend was found from 1982 to 2013 (Ding et al, ; Liu et al, ). Ding et al () used the polynomial method and the GIMMS3g (version 0) and SPOT‐VEG data, while Liu et al () used the logistic method (logistic fitting and NDVI inflection detecting) and the advanced very high resolution radiometer (AVHRR) and MODIS data. T. Wang et al () found that the continuously advancing trend in SOS derived from MODIS and SPOT‐VEG NDVI was significantly correlated with the increasing NDVI in January–April induced by the deceasing snow cover fraction.…”

Section: Introductionmentioning

confidence: 84%

No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau

Wang

Xiao

et al. 2017

JGR Biogeosciences

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Vegetation phenology is a sensitive indicator of climate change and has significant effects on the exchange of carbon, water, and energy between the terrestrial biosphere and the atmosphere. The Tibetan Plateau, the Earth's “third pole,” is a unique region for studying the long‐term trends in vegetation phenology in response to climate change because of the sensitivity of its alpine ecosystems to climate and its low‐level human disturbance. There has been a debate whether the trends in spring phenology over the Tibetan Plateau have been continuously advancing over the last two to three decades. In this study, we examine the trends in the start of growing season (SOS) for alpine meadow and steppe using the Global Inventory Modeling and Mapping Studies (GIMMS)3g normalized difference vegetation index (NDVI) data set (1982–2014), the GIMMS NDVI data set (1982–2006), the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data set (2001–2014), the Satellite Pour l'Observation de la Terre Vegetation (SPOT‐VEG) NDVI data set (1999–2013), and the Sea‐viewing Wide Field‐of‐View Sensor (SeaWiFS) NDVI data set (1998–2007). Both logistic and polynomial fitting methods are used to retrieve the SOS dates from the NDVI data sets. Our results show that the trends in spring phenology over the Tibetan Plateau depend on both the NDVI data set used and the method for retrieving the SOS date. There are large discrepancies in the SOS trends among the different NDVI data sets and between the two different retrieval methods. There is no consistent evidence that spring phenology (“green‐up” dates) has been advancing or delaying over the Tibetan Plateau during the last two to three decades. Ground‐based budburst data also indicate no consistent trends in spring phenology. The responses of SOS to environmental factors (air temperature, precipitation, soil temperature, and snow depth) also vary among NDVI data sets and phenology retrieval methods. The increases in winter and spring temperature had offsetting effects on spring phenology.

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“…Lower density of surface observation networks, higher altitudes and complex and diverse natural environments, and vegetation types might be responsible for the inconsistent distributions. Ding et al [2] analyzed the relationship between the start of the growing season and temperature and precipitation over the Tibetan Plateau and found regions with significant delay for the start of the growing season were mostly distributed in the semi-arid areas, while regions with significant advance of the start were mainly scattered in humid and semi-humid areas from 1982 to 2012. In relatively humid area, the start of the growing season was significantly correlated with spring temperature, and the importance of spring temperature gradually decreased with increasing aridity.…”

Section: Discussionmentioning

confidence: 99%

“…3-4.8 ∘ C relative to 1986-2005 [1]. Changes in the vegetation growing season have received much attention as the timing and length of the growing season are sensitive to climate variation and global warming [2,3], and changes in the growing season can also affect the function and service of ecosystems (e.g., agricultural production, carbon sequestration potential, soil and water conservation, and biological diversity) and global and regional climate [4][5][6]. An increasing number of studies, based on climatological, phonological, and satellite remote sensing data, have reported an earlier spring, later autumn, and consequently prolonged growing season over most of the Northern Hemisphere in the twentieth century [1,6], though the earlier onset of the growing season was slowed down in the first decade of the twenty-first century [3].…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Thermal Growing Season Indices for the Northern China during 1961–2015

Cui

Shi

2017

Advances in Meteorology

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Vegetation phenology is one of the most direct and sensitive indicators of terrestrial ecosystem in response to climate change. Based on daily mean air temperature at 877 meteorological stations over northern China from 1961 to 2015, the correlations and differences for different definitions of the growing season parameters (start, end, and length of the growing season) were investigated, and results show that higher correlations of 0.81-0.93 are found when indices which do not consider frost are compared with those of the same length which include the frost criteria, and lower correlations of 0.63-0.79 are observed when the length of indices is different and one of the indices includes the frost criteria or EI 3 (10 d < 5 ∘ C) is included. Lower correlations and larger differences are generally observed in the eastern and northwestern parts while higher correlation and smaller difference appeared in the northeastern and southwestern parts of northern China; thus the applicability comparison and selection of different definitions have important influence on the identifying and counting of the timing and length of the growing season in the eastern and northwestern regions of northern China.

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Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012

Abstract: Abstract

Cited by 25 publications

References 57 publications

Heterogeneous spring phenology shifts affected by climate: supportive evidence from two remotely sensed vegetation indices

Heterogeneous spring phenology shifts affected by climate: supportive evidence from two remotely sensed vegetation indices

No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau

A Comparison of Thermal Growing Season Indices for the Northern China during 1961–2015

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