Dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China

Li, Peng; Peng, Changhui; Wang, Meng; Luo, Yunpeng; Li, Mingxu; Zhang, Kerou; Zhang, Dingling; Zhu, Qiuan

doi:10.1016/j.scitotenv.2018.05.031

Cited by 82 publications

(50 citation statements)

References 86 publications

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“…Our analysis using remote sensing NDVI time series from multiple sources indicated that there was no significant temporal trend in DOD during the entire research period. Based on NDVI remote sensing data, several previous studies also reported a nonsignificant temporal trend of DOD in the vegetation of QTP (Yang et al, 2015;Li et al, 2018). Our research indicated that opposing trends between the southwestern QTP and other areas lead to nonsignificant temporal trends in the DOD over the entire study area.…”

Section: Change In Vegetation Dormancy On the Qtpsupporting

confidence: 63%

“…We noticed that the DOD had a delayed trend after 1997; this may due to the large-scale conservation programs implemented by the Chinese government, including the Natural Forest Conservation Program (initiated in 1998) and the Grain for Green Program (initiated in 1999) (Liu et al, 2008), which protect the vegetation from interference of human and lead to an increase in vegetation cover. Because the increase of vegetation cover can increase the amount of solar radiation absorbed by the surface through reduced albedo, which could produce a climate warming effect (Pearson et al, 2013), resulting in a delayed vegetation dormancy (Li et al, 2018). The last turning point of 2007 could be explained by the complicated interaction between the increasing temperature and decreasing precipitation during this period.…”

Section: Change In Vegetation Dormancy On the Qtpmentioning

confidence: 99%

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Change in Autumn Vegetation Phenology and the Climate Controls From 1982 to 2012 on the Qinghai–Tibet Plateau

Zhu

Peng

et al. 2020

Front. Plant Sci.

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Autumn vegetation phenology plays a critical role in the survival and reproduction of vegetation in changing environments. Using GIMMS3g (Global Inventory Modeling and Mapping Studies), MODIS (Moderate Resolution Imaging and Spectroradiometer), and SPOT (Systeme Probatoire d'Observation de la Terre) remote sensing data, we investigated the spatial and temporal dynamics of the vegetation dormancy onset date (DOD) and its response to temperature, precipitation, and cold degree days (CDD) in different biomes on the Qinghai-Tibet Plateau (QTP) from 1982 to 2012. Our results indicated that there was no significant temporal trend in the DOD for the vegetation on the QTP but found clear regional characteristics in the DOD trends with a notably advancing trend in the central region and a widespread delay in the southwestern region (>1 day year −1 , P < 0.05). Our results also indicated that temperature plays an important role in the trend of delays in vegetation autumn phenology; in particular, the preseason temperature can delay the DOD significantly; the positive correlations were observed in more than 71% of the study areas. Consistent with previous studies, we observed significant negative correlations between preseason CDD and DOD; the negative correlations were observed in more than 72% of the study areas for all the data sets. In contrast, the effects of precipitation on DOD were biome dependent. We found that precipitation could promote the extension of the growing season in meadow and grass biomes but produce weak effects on vegetation dormancy in forest biomes. Therefore, not only the magnitude but also the timing of changes in temperature and precipitation determines the effects of climate factors on DOD and further suggests that biome-specific phenological responses also need to be integrated into vegetation phenology models for future climate change investigations on the QTP.

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Section: Change In Vegetation Dormancy On the Qtpsupporting

confidence: 63%

Section: Change In Vegetation Dormancy On the Qtpmentioning

confidence: 99%

Change in Autumn Vegetation Phenology and the Climate Controls From 1982 to 2012 on the Qinghai–Tibet Plateau

Zhu

Peng

et al. 2020

Front. Plant Sci.

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“…The relationships between plant autumn phenology and climatic factors are more complicated than with the spring phenology [15] and its mechanisms are still not clear [14,16,17]. Based on partial correlation or regression analysis, temperature, precipitation, and insolation are considered to be important climatic factors affecting the autumn phenology of herbaceous plants on the QTP [7,8,18,19]. However, the relative importance of each factor is not known.…”

Section: Introductionmentioning

confidence: 99%

“…However, the relative importance of each factor is not known. Among them, temperature is commonly thought to be the most important driver; the higher the average preseason temperature, the later the autumn phenology [7,8,[19][20][21]. Precipitation and sunshine duration are secondary influence factors, but the results from different studies are inconsistent.…”

Section: Introductionmentioning

confidence: 99%

Precipitation and Minimum Temperature are Primary Climatic Controls of Alpine Grassland Autumn Phenology on the Qinghai-Tibet Plateau

Chen

Zhang

et al. 2020

Remote Sensing

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Autumn phenology is a crucial indicator for identifying the alpine grassland growing season’s end date on the Qinghai-Tibet Plateau (QTP), which intensely controls biogeochemical cycles in this ecosystem. Although autumn phenology is thought to be mainly influenced by the preseason temperature, precipitation, and insolation in alpine grasslands, the relative contributions of these climatic factors on the QTP remain uncertain. To quantify the impacts of climatic factors on autumn phenology, we built stepwise linear regression models for 91 meteorological stations on the QTP using in situ herb brown-off dates, remotely sensed autumn phenological metrics, and a multi-factor climate dataset during an optimum length period. The results show that autumn precipitation has the most extensive influence on interannual variation in alpine grassland autumn phenology. On average, a 10 mm increase in autumn precipitation during the optimum length period may lead to a delay of 0.2 to 4 days in the middle senescence date (P < 0.05) across the alpine grasslands. The daily minimum air temperature is the second most important controlling factor, namely, a 1 °C increase in the mean autumn minimum temperature during the optimum length period may induce a delay of 1.6 to 9.3 days in the middle senescence date (P < 0.05) across the alpine grasslands. Sunshine duration is the third extensive controlling factor. However, its influence is spatially limited. Moreover, the relative humidity and wind speed also have strong influences at a few stations. Further analysis indicates that the autumn phenology at stations with less autumn precipitation is more sensitive to precipitation variation than at stations with more autumn precipitation. This implies that autumn drought in arid regions would intensely accelerate the leaf senescence of alpine grasslands. This study suggests that precipitation should be considered for improving process-based autumn phenology models in QTP alpine grasslands.

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“…Change point first occurs in the northern and then in the southern region across mainland The Fifth Assessment Report of the Intergovernmental Panel on Climate Change showed that the global climate has increased by 0.85 C (0.65−1.06 C) in surface air temperature during 1880-2012 (Myhre et al, 2013). Global warming poses a potentially significant threat to human and natural systems, for instance the crop yield (Lesk et al, 2016;Asseng et al, 2014;Zhang et al, 2017b), plant phenology (Guo et al, 2018a;Li et al, 2018a), land degradation (Wang et al, 2017c), water resources management (Venkataraman et al, 2016), energy, labour, and human mortality (Hsiang et al, 2017) etc. The frequency and severity of heat waves (HWs) are also anticipated to increase as a consequence of climate change.…”

mentioning

confidence: 99%

Assessing spatiotemporal variation of heat waves during 1961–2016 across mainland China

Guo

Wang

Bao

2019

Intl Journal of Climatology

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Heat waves (HWs) are one of the current topics of scientific research in the context of global warming, as they can have a disastrous impact on both environment and society. Therefore, detailed studies of variations of HWs that assess variability on spatiotemporal scales are becoming increasingly necessary.The main objective of this study is to detect and analyse variation in HWs and potential climate drivers across China based on Köppen climate classifications. Daily observation data (maximum and minimum temperature) from 1961 to 2016 were used in the study to define HWs based on excess heat factors (EHFs). Linear trend analysis, Bayesian change-point analysis, cross-wavelet

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Dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China

Cited by 82 publications

References 86 publications

Change in Autumn Vegetation Phenology and the Climate Controls From 1982 to 2012 on the Qinghai–Tibet Plateau

Change in Autumn Vegetation Phenology and the Climate Controls From 1982 to 2012 on the Qinghai–Tibet Plateau

Precipitation and Minimum Temperature are Primary Climatic Controls of Alpine Grassland Autumn Phenology on the Qinghai-Tibet Plateau

Assessing spatiotemporal variation of heat waves during 1961–2016 across mainland China

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