Delayed autumn leaf senescence date prolongs the growing season length of herbaceous plants on the Qinghai–Tibetan Plateau

Sun, Qingling; Li, Baolin; Zhou, Guoyi; Jiang, Yuhao; Yuan, Yecheng

doi:10.1016/j.agrformet.2019.107896

Cited by 43 publications

(34 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We found that the rate of the delaying EOS increased from 0.02--0.09 daysÁdecade −1 in the period 1982-2011 (Figure S3c) to 0.06-0.17 daysÁdecade −1 within 1982-2018 (Figure 3). A similar pattern was also observed after the year 2011 using a large number of observational records (Zhu et al, 2017;Sun et al, 2020b), which also confirmed the importance of continuously tracing the latest variation of EOS under the ongoing climate change.…”

Section: The Trend Of Eos On the Tpsupporting

confidence: 79%

“…(2017) and Sun et al . (2020b) found that the autumn phenology of herbaceous plants significantly delayed at rates of 2.4 days·decade −1 (1981–2011) and 5.29 days·decade −1 (1981–2017), respectively, on the TP based on large numbers of ground observations. Supported by satellite data, most studies also demonstrated nonsignificant but delayed trends of EOS on the TP with the average rates of 2.18 days·decade −1 during 1999–2009 ( p = .61) (Ding et al ., 2013), around 0.5 days·decade −1 during 1982–2011 ( p ≥ .05) (Liu et al ., 2016a), 0.70 days·decade −1 during 1982–2011 ( p = .18) (Cong et al ., 2017), 0.15 days·decade −1 during 1982–2012 ( p = .75) (Ding et al ., 2016), and 0.41 days·decade −1 during 1982–2014 ( p = .08) (Che et al ., 2014).…”

Section: Discussionmentioning

confidence: 99%

“…The overall delaying trend in EOS is consistent with most previous studies based on both in situ observations and satellitederived autumn phenology. For example, Zhu et al (2017) and Sun et al (2020b) found that the autumn phenology of herbaceous plants significantly delayed at rates of 2.4 daysÁdecade −1 (1981-2011) and 5.29 daysÁdecade −1 (1981-2017), respectively, on the TP based on large numbers of ground observations. Supported by satellite data, most studies also demonstrated nonsignificant but delayed trends of EOS on the TP with the average rates of 2.18 daysÁdecade −1 during 1999-2009 (p = .61) (Ding et al, 2013) 1982-2011 (p = .18) (Cong et al, 2017), 0.15 daysÁdecade −1 during 1982-2012 (p = .75) (Ding et al, 2016), and 0.41 daysÁdecade −1 during 1982-2014 (p = .08) (Che et al, 2014).…”

Section: The Trend Of Eos On the Tpmentioning

confidence: 99%

“…Substantial studies and continuous debate have arisen about the shift in spring phenology (Yu et al, 2010;Shen et al, 2013;Zhang et al, 2013), but less attention was paid to autumn phenology (Shen et al, 2015). Recently, delayed trends in EOS have been observed from both in situ observations and satellite data (Ding et al, 2013;Che et al, 2014;Ding et al, 2016;Liu et al, 2016a;Cong et al, 2017;Zhu et al, 2017;Sun et al, 2020b), while earlier EOS was also reported by satellite observations (Yang et al, 2015;Zu et al, 2018;Li et al, 2020). Besides, there are discrepancies among EOS trends for different vegetation types (Yu et al, 2010;Che et al, 2014;Zhu et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau

Peng

Wang

et al. 2021

Intl Journal of Climatology

View full text Add to dashboard Cite

As the third pole of the Earth, the Tibetan Plateau (TP) is highly sensitive to climate change. Phenological changes in spring (i.e., the start of the growing season, SOS) over the TP are of much debate, while our understanding on the variation of autumn phenology (i.e., the end of the growing season, EOS) is still lacking. Given the significance of tracing the latest variation of EOS induced by the ongoing global change, we used the currently longest time series of the normalized difference vegetation index of the Long Term Data Record from the Advanced Very High Resolution Radiometer (AVHRR LTDR NDVI) and investigated the responses of EOS to biological and climatic factors. We found that the EOS showed an insignificantly delayed trend at an average rate of 0.14 daysÁdecade −1 on the TP. This variation was found for all vegetation types except for alpine sparse vegetation. We further showed that spring SOS had the largest contribution to the interannual variations in EOS, where 46.5% of the vegetated areas showed significantly positive correlations between SOS and EOS (p < .05). Temperature (26.5%) and precipitation (18.8%) also had significant positive impacts on EOS, while the contribution of radiation was negative (11.3%). These correlations were regulated by local hydrothermal conditions, especially for precipitation gradients. Using the longest satellite data currently available, with the state-of-art data processing, we demonstrated a weakly delaying trend of EOS and the controlling role of spring phenology on the interannual variability of EOS, which is of great significance to improve our comprehension of the interactions between vegetation dynamics and climate change in the future.

show abstract

Section: The Trend Of Eos On the Tpsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Section: The Trend Of Eos On the Tpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau

Peng

Wang

et al. 2021

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…The extreme low temperature on the TP is a long-term stress factor, and the low productivity is understandable. Low temperature can inhibit the activity of plant cell enzymes, resulting in slower plant growth and limited organic matter accumulation during the short period in which the soil thaws [44]. In addition, the alpine vegetation on the TP is more dwarf PLOS ONE [45], and grows in a unique high-density "straw felt" pattern, allowing plants to gather together for warmth.…”

Section: Plos Onementioning

confidence: 99%

Regional response of grassland productivity to changing environment conditions influenced by limiting factors

Hou

Yan

et al. 2020

PLoS ONE

View full text Add to dashboard Cite

Regional differences and regulatory mechanisms of vegetation productivity response to changing environmental conditions constitute a core issue in macroecological researches. To verify the main limiting factors of different macrosystems [temperature-limited Tibetan Plateau (TP), precipitation-limited Mongolian Plateau (MP), and nutrient-limited Loess Plateau (LP)], we conducted a comparative survey of the east-west grassland transects on the three plateaus and explored the factors limiting regional productivity and their underlying mechanisms. The results showed that aboveground net primary productivity (ANPP) of LP (109.10 ± 16.76 g m −2 yr −1 ) was significantly higher than that of MP (66.71 ± 11.11 g m −2 yr −1 ) and TP (57.02 ± 10.59 g m −2 yr −1 ). The response rate of ANPP with environmental changes was different among different plateaus, being closely related to the main limiting factors. On MP, this was precipitation, on LP it was temperature and nutrients, and on TP, it was non-specific, reflecting restriction by the extremely low temperature. After autocorrelation screening of environmental factors, different regions exhibited different productivity response mechanisms. MP was mainly influenced by temperature and precipitation, LP was influenced by temperature and nutrient, and TP was influenced by nutrient, reflecting the modifying effect of the main limiting factors. The effect of each regional environment on ANPP was 72.56% on average and only 27.18% after simple regional integration. The regional model could optimize the simulation error of the integrated model, and the relative deviations in MP, LP, and TP were reduced by 31.76%, 17.22%, and 2.23%, respectively. These findings indicate that the grasslands on the three plateaus may have different or even the opposite mechanisms to control productivity.

show abstract

Effects of disturbances on aboveground biomass of alpine meadow in the Yellow River Source Zone, Western China

Yan

Gao

et al. 2022

Ecology and Evolution

View full text Add to dashboard Cite

A field experiment quantifies the impacts of two external disturbances (mowing‐simulated grazing and number of pika) on aboveground biomass (AGB) in the Yellow River Source Zone from 2018 to 2020. AGB was estimated from drone images for 27 plots subject to three levels of each disturbance (none, moderate, and severe). The three mowing severities bear a close relationship with AGB and its annual change. The effects of pika disturbance on AGB change were overwhelmed by the significantly different AGB at different mowing severities (−.471 < r < −.368), but can still be identified by inspecting each mowing intensity (−.884 < r < −.626). The impact of severe mowing on AGB loss was more profound than that of severe pika disturbance in heavily disturbed plots, and the joint effects of both severe disturbances had the most impacts on AGB loss. However, pika disturbance made little difference to AGB change in the moderate and non‐mowed plots. Mowing intensity weakens the relationship between pika population and AGB change, but pika disturbance hardly affects the relationship between mowing severity and AGB change. The effects of both disturbances on AGB were further complexified by the change in monthly mean temperature. Results indicate that reducing mowing intensity is more effective than controlling pika population in efforts to achieve sustainable grazing of heavily disturbed grassland.

show abstract

Delayed autumn leaf senescence date prolongs the growing season length of herbaceous plants on the Qinghai–Tibetan Plateau

Cited by 43 publications

References 52 publications

Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau

Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau

Regional response of grassland productivity to changing environment conditions influenced by limiting factors

Effects of disturbances on aboveground biomass of alpine meadow in the Yellow River Source Zone, Western China

Contact Info

Product

Resources

About