Field evidence for earlier leaf-out dates in alpine grassland on the eastern Tibetan Plateau from 1990 to 2006

Zhou, Hua; Yao, Buqing; Xu, Wenhua; Ye, X.; Fu, Jinzhong; Jin, Yingshuai; Zhao, Xinquan

doi:10.1098/rsbl.2014.0291

Cited by 23 publications

(11 citation statements)

References 27 publications

(33 reference statements)

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“…This approach is relatively flexible [52,53] with fewer data requirements than other PET estimation approaches, which provides advantages in the Tibetan Plateau which has very limited in situ surface meteorology observations. As the growing season of the TP grasslands generally starts around May [5,25,35,54], we used the period from March to May to represent pre-season climate conditions for spring onset. The use of partial correlation analysis allows for distinguishing phenological effects from individual environmental variables while accounting for the interactive effects of other contributing variables.…”

Section: Discussionmentioning

confidence: 99%

“…Over 80% of the study area (4592˘510 m) ranges between 4300 and 5000 m in elevation, and ecosystems within this elevation zone likely experience an earlier green-up of 6-8 days in response to a 1˝C rise in May air temperatures [16]. In-situ observations have documented different spring leaf-out dates between the TP meadow and steppe grasslands [35], so we divided the study domain into three sub-areas based on regional eco-geographic attributes [30]. Among the three eco-zones examined, Zone-3 is the warmest with a mean annual air temperature (T a ) of´1.07˝C, followed by Zone-2 (´3.83˝C) and Zone-1 (´4.67˝C).…”

Section: Study Areamentioning

confidence: 99%

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Climatic Controls on Spring Onset of the Tibetan Plateau Grasslands from 1982 to 2008

Zhang

Kimball

et al. 2015

Remote Sensing

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Understanding environmental controls on vegetation spring onset (SO) in the Tibetan Plateau (TP) is crucial to diagnosing regional ecosystem responses to climate change. We investigated environmental controls on the SO of the TP grasslands using satellite vegetation index (VI) from the 3rd Global Inventory Modeling and Mapping Studies (GIMMS3g) product, with in situ air temperature (T a ) and precipitation (Prcp) measurement records from 1982 to 2008. The SO was determined using a dynamic threshold method based on a 25% threshold of seasonal VI amplitude. We find that SO shows overall close associations with spring T a , but is also subject to regulation from spring precipitation. In relatively dry but increasingly wetting (0.50 mm¨year´1, p < 0.10) grasslands (mean spring Prcp = 22.8 mm; T a =´3.27˝C), more precipitation tends to advance SO (´0.146 day¨mm´1, p = 0.150) before the mid-1990s, but delays SO (0.110 day¨mm´1, p = 0.108) over the latter record attributed to lower solar radiation and cooler temperatures associated with Prcp increases in recent years. In contrast, in relatively humid TP grasslands (73.0 mm;´3.51˝C), more precipitation delays SO (0.036 day¨mm´1, p = 0.165) despite regional warming (0.045˝C¨year´1, p < 0.05); the SO also shows a delaying response to a standardized drought index (mean R = 0.266), indicating a low energy constraint to vegetation onset. Our results highlight the importance of surface moisture status in regulating the phenological response of alpine grasslands to climate warming.

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Section: Discussionmentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

Climatic Controls on Spring Onset of the Tibetan Plateau Grasslands from 1982 to 2008

Zhang

Kimball

et al. 2015

Remote Sensing

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“…The observed remote sensing patterns are interesting, yet they are unable to tease apart the mechanisms driving the observed changes in phenology because they are not experimental and they cannot detect flowering (Shen et al., ; Wang, Meng, et al., ). Moreover, some experimental and observational studies have revealed that warming accelerated the phenology on the Tibetan Plateau (Chen et al., ; Meng et al., ; Wang, Meng, et al., ; Wang, Wang, et al., ; Zhou et al., ). Given asymmetric warming on plant phenology has been unexplored, it remains unclear how differences in winter and spring temperatures control spring phenology.…”

Section: Introductionmentioning

confidence: 99%

Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow

et al. 2017

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The warming of terrestrial high‐latitude ecosystems, while increasing, will likely be asymmetric across seasons—where winter non‐growing seasons will warm more than summer‐growing seasons. Asymmetric winter warming in temperature‐sensitive ecosystems may delay spring phenological events by reducing the opportunity that a plants’ chilling requirement is met. Similarly, symmetric warming can advance spring phenology. To explore the impact of asymmetric warming on plant phenology, we applied a year‐round warming and a winter warming treatment to our experimental plots. Over a 2‐year period, we monitored leaf‐out and flowering phenology for 11 plant species. There was variation among species, however, both winter and year‐round warming, advanced the leaf‐out day and the first flowering day relative to the control treatment. Winter warming advanced leaf‐out and flowering phenology by 11.1 (±2.4) and 12.6 (±2.9) days respectively. However, year‐round warming had less of an impact advancing leaf‐out and flowering phenology by 5.1 (±2.1) and 10.0 (±3.0) days respectively. Our study provides direct evidence that asymmetric winter warming has a larger impact on plant phenology than symmetric year‐round warming. Increasing soil temperature in the winter from below to above freezing temperatures advanced the spring phenology of alpine plants. Winter warming increased soil temperature more than year‐round warming, which explains why phenology advanced under winter warming more than under year‐round warming. In addition, early or mid‐season flowering plant species displayed different phenology strategies in warmer winters. Relative to other ecosystems, alpine ecosystems such as the Tibetan Plateau will likely respond to asymmetric warming given the higher amplitude of winter temperature increases due to climatic warming. Our data indicate that seasonal variation in warming should be considered when predicting and modelling the response of alpine ecosystems to climatic change. A http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.12909/suppinfo is available for this article.

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“…Statistically significant temporal trends in long-term phenological time series are not always detected using a linear regression model because phenological changes may not exhibit a monotonic trend (Menzel et al 2006, Shen et al 2014, Zhou et al 2014. However, unlike linear regression SSA does not impose linearity on the time series and has been successfully used to describe the complex variation in spring phenology of Figure 9.…”

Section: Discussionmentioning

confidence: 99%

Detecting spatiotemporal changes of peak foliage coloration in deciduous and mixedforests across the Central and Eastern United States

Liu

Zhang

et al. 2017

Environ. Res. Lett.

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The timing of fall foliage coloration, especially peak coloration, is of great importance to the climate change research community as it has implications for carbon storage in forests. However, its longterm variation and response to climate change are poorly understood. To address this issue, we examined the long-term trends and breakpoints in satellite derived peak coloration onset from 1982 to 2014 using an innovative approach that combines Singular Spectrum Analysis (SSA) with Breaks for Additive Seasonal and Trend (BFAST). The peak coloration trend was then evaluated using both field foliage coloration observations and flux tower measurements. Finally, interannual changes in peak coloration onset were correlated with temperature and precipitation variation. Results showed that temporal trends in satellite-derived peak coloration onset were comparable with both field observations and flux tower measurements of gross primary productivity. Specifically, a breakpoint in long-term peak coloration onset was detected in 25% of pixels which were mainly distributed at latitudes north of 37°N. The breakpoint tended to occur between 1998 and 2004. Peak coloration onset was delayed before the breakpoint while it was transformed to an early trend after the breakpoint in nearly all pixels. The remaining 75% of pixels exhibited monotonic trends, 35% of which revealed a late trend and 40% an early trend. The results indicate that the onset of peak coloration experienced a late trend during the 1980s and 1990s in most deciduous and mixed forests. However, the trend was reversed during the most recent decade when the timing of peak coloration became earlier. The onset of peak coloration was significantly correlated with late summer and autumn temperature in 55.5% of pixels from 1982 to 2014. This pattern of temperature impacts was also verified using field observations and flux tower measurements. In the remaining 44.5% of pixels, 12.2% of pixels showed significantly positive correlation between the onset of peak coloration and cumulative precipitation during late summer and autumn period from 1982 to 2014. Our findings can improve understanding of the impact of changes in autumn phenology on carbon uptake in forests, which in turn facilitate more reliable measures of carbon dynamics in vegetation-climate interactions models.

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Field evidence for earlier leaf-out dates in alpine grassland on the eastern Tibetan Plateau from 1990 to 2006

Cited by 23 publications

References 27 publications

Climatic Controls on Spring Onset of the Tibetan Plateau Grasslands from 1982 to 2008

Climatic Controls on Spring Onset of the Tibetan Plateau Grasslands from 1982 to 2008

Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow

Detecting spatiotemporal changes of peak foliage coloration in deciduous and mixedforests across the Central and Eastern United States

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