Increasing contamination might have delayed spring phenology on the Tibetan Plateau

Yi, Shuai; Zhou, Zhengchao

doi:10.1073/pnas.1100394108

Cited by 39 publications

(25 citation statements)

References 4 publications

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“…The data quality issues of GIMMS NDVI in the Tibetan Plateau mainly occur in April, May, and June (especially in May), which overlaps the period of vegetation green-up and would thus affect the vegetation phenology retrieved. Although the deviation of the GIMMS NDVI is relatively low due to the absolute low NDVI values in the alpine grassland, it could cause a relatively large error in retrieving the vegetation SOS (19).…”

Section: Discussionmentioning

confidence: 99%

“…Several recent studies using AVHRR NDVI time-series data have reported that the alpine steppe and meadow also underwent an SOS advancement from 1982 to the end of the 1990s, but an SOS delay was found from the end of the 1990s to 2006 (10,11,15,17). Several explanations for this trend of reversal were proposed but remain controversial (10,11,15,(17)(18)(19)(20)(21). One study based on MODIS NDVI data showed that the alpine vegetation SOS advanced in 60% of this region in the Northern Tibetan Plateau from 2001 to 2010 (22).…”

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confidence: 99%

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Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011

Zhang

Dong

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

561

384

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As the Earth’s third pole, the Tibetan Plateau has experienced a pronounced warming in the past decades. Recent studies reported that the start of the vegetation growing season (SOS) in the Plateau showed an advancing trend from 1982 to the late 1990s and a delay from the late 1990s to 2006. However, the findings regarding the SOS delay in the later period have been questioned, and the reasons causing the delay remain unknown. Here we explored the alpine vegetation SOS in the Plateau from 1982 to 2011 by integrating three long-term time-series datasets of Normalized Difference Vegetation Index (NDVI): Global Inventory Modeling and Mapping Studies (GIMMS, 1982–2006), SPOT VEGETATION (SPOT-VGT, 1998–2011), and Moderate Resolution Imaging Spectroradiometer (MODIS, 2000–2011). We found GIMMS NDVI in 2001–2006 differed substantially from SPOT-VGT and MODIS NDVIs and may have severe data quality issues in most parts of the western Plateau. By merging GIMMS-based SOSs from 1982 to 2000 with SPOT-VGT–based SOSs from 2001 to 2011 we found the alpine vegetation SOS in the Plateau experienced a continuous advancing trend at a rate of ∼1.04 d·y −1 from 1982 to 2011, which was consistent with observed warming in springs and winters. The satellite-derived SOSs were proven to be reliable with observed phenology data at 18 sites from 2003 to 2011; however, comparison of their trends was inconclusive due to the limited temporal coverage of the observed data. Longer-term observed data are still needed to validate the phenology trend in the future.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011

Zhang

Dong

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

561

384

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“…Chen et al [49] believed that, on the regional scale, the possible delayed spring phenology in the meadow and steppe should be attributed not only to winter and spring warming but also to grassland degradation, thawing-freezing process, and their combined effects. Yi and Zhou [50] believed that changes in contamination played an important role in the retrieval of NDVI, resulting in phenology delay. The current paper suggests that such delay is closely related to the difference in the analyzed temporal scale because the time series leading to such conclusion is in 1999-2006.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009

et al. 2012

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Plant phenology is the most salient and sensitive indicator of terrestrial ecosystem response to climate change. Studying its change is significantly important in understanding and predicting impressively changes in terrestrial ecosystem. Based on NDVI from SPOT VGT, this paper analyzed the spatiotemporal changes in alpine grassland phenology in Qinghai-Tibetan Plateau from 1999 to 2009. The results are enumerated as follows: (1) The spatial distribution of the average alpine grassland phenology from 1999 to 2009 is closely related to water and heat conditions. Accompanying the deterioration in heat and water conditions from southeast to northwest, the start of growth season (SOG) was delayed gradually, the end of growth season (EOG) advanced slowly, and the length of growth season (LOG) shortened gradually. Elevation played an important role in the regional differentiation of phenology, but a dividing line of approximately 3500 m existed. Below this line, the phenology fluctuated irregularly with altitude change, whereas above the line, the phenology is closely related to altitude change. (2) From 1999 to 2009, SOG of the alpine grassland came earlier by six days per decade (R 2 =0.281, P=0.093), EOG was late by two days per decade (R 2 =0.031, P=0.605), and LOG lengthened by eight days per decade (R 2 =0.479, P=0.018). The early SOG, the late EOG, and the extended LOG mainly occurred at the center and east of the Plateau. SOG in most of the Plateau advanced significantly, especially in the eastern Plateau. (3) The inter-annual phenology changes of the alpine grassland in the Qinghai-Tibetan Plateau exhibited significant differentiation at different elevation and natural zones. The inter-annual changes at high altitude were more complicated than that at low altitude. The most significant phenology changes were found in the eastern Qinghai-Qilian montane steppe zone, and non-significant changes occurred in the Southern Tibet montane shrub-steppe zone. . Plant phenology not only provides a substantial theoretical and practical significance in farming forecast, agricultural and animal-husbandry production guidance, pest indication, seed introduction and selection, and many other aspects but also serves as an important parameter in land process model and global vegetation model [3][4][5][6]. Qinghai-TibetanThis information is very important in promoting people's understanding of the response of vegetation to climate change and improving the simulation accuracy of mass and energy exchanges between the atmosphere and vegetation [7]. As the best indicator in monitoring the influence of climate on vegetation, plant phenology has become the key point of global-change research [8]. Plant phenology analysis based on remote sensing data shows that the growth season of plants in northern hemisphere has lengthened gradually during the last decades [9][10][11][12]. These conclusions are supported by ground observation data. The spring phenophase of most plants in Europe and North America have

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“…controversy regarding the rate and amplitude of change in TP spring phenology, and the extent to which climatic drivers were responsible for any of these purported changes (10,(14)(15)(16). It has been suggested that the observed delay in spring growth detected from the mid-1990s to 2006 was a measurement artifact due to the reduced quality of the AVHRR NDVI data since 2001 (9).…”

Section: Significancementioning

confidence: 99%

“…It is claimed that satellite-derived vegetation indices are easily contaminated by adverse atmospheric conditions, such as varying aerosol concentrations (10,15). Other background factors, including changes in snow cover (16) or vegetation coverage due to grassland degradation and/or freezing−thawing cycles (10,14), have been identified as possible causes of inaccuracy, especially in cases in which the signal is weak in vegetation green-up times detected by satellites (13).…”

Section: Significancementioning

confidence: 99%

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

Yang

Shishov

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

208

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Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world's largest highelevation region. This study provides a perspective on vegetation phenology shifts during 1960-2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0. April-June and August-September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1°C in April-June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale.tree rings | cambial activity | plant phenology | climate change | Tibetan Plateau P henology has a profound impact on vegetation growth (1), carbon balances of terrestrial ecosystems (2), and climate change feedback mechanisms (3). The importance of phenology has prompted many studies, mainly using ground-based observations (4-7), which provide useful phenological information at the species level. However, such studies are also quite time-intensive and typically focus on a few individuals in restricted geographic areas, which often limits their applicability to larger spatiotemporal scales. Changes in plant phenology can be detected on larger spatial scales through near-surface remote sensing, using digital repeat photography (8), but this approach remains limited to the stand level. Another commonly used approach is satellite remote sensing, which can cover large areas (9-11); however, this method has yielded inconsistent results on the Tibetan Plateau (TP) (9, 12, 13).The TP, with an average altitude of over 4,000 m above sea level (a.s.l.), covers more than 2 million square kilometers and is strongly affected by ongoing climate change. Due to its vast area, and its position in subtropical latitudes with high incoming solar radiation, changes in vegetation period duration may have major consequences for regional climate and for carbon sequestration in SignificanceInconsistent results regarding the rate of change in spring phenology and its relation to climatic drivers on the Tibetan Plateau have been obtained in the past. We introduce and describe here an innovative approach based on tree-ring data, which converts daily weather data into indices of the start (and end) of the growing season. This method pro...

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Increasing contamination might have delayed spring phenology on the Tibetan Plateau

Cited by 39 publications

References 4 publications

Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011

Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011

Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009

New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

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