Climate warming shifts the time interval between flowering and leaf unfolding depending on the warming period

Wang, Shuxin; Wu, Zhaofei; Gong, Yufeng; Wang, Shubiao; Zhang, Wei; Zhang, Shanshan; Boeck, Hans J. De; Fu, Yulan

doi:10.1007/s11427-022-2094-6

Cited by 7 publications

(6 citation statements)

References 46 publications

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“…where T day is the mean daily temperature from 1 November to the leaf-out date (including both field and indoor conditions), and T base is the base temperature of 0°C following ref (Wang et al, 2022). The spatial variation in RSP and the limitations in winter chilling and photoperiod along gradients of MAT, MAP, and the seasonalities of temperature and precipitation were estimated using linear or nonlinear regression analysis.…”

Section: Discussionmentioning

confidence: 99%

“…Each chamber was split into two parts using shade cloth, allowing us to apply two photoperiod treatments: daylengths of 10 and 14 h (Wu et al ., 2022a). Two chilling treatments were applied by collecting twigs early (19 December 19; Low chilling) and late (1 March 2022; High chilling) in winter to cause different exposure of twigs to outdoor winter conditions (Zohner et al ., 2016; Wang et al ., 2022). This setup had 16 treatment combinations (2 chilling × 4 temperature × 2 photoperiod treatments).…”

Section: Methodsmentioning

confidence: 99%

“…The extent of chilling limitation was calculated based on the leaf‐out difference (in days) between the twigs cultivated under low (early collection) and high chilling (late collection), and the extent of photoperiod limitation was calculated using the leaf‐out difference between the twigs cultivated under short‐ and long‐day conditions. The heat requirement (growing degree days, GDD) of each twig to achieve leaf‐out was calculated using a sigmoidal function:

GDD = \sum_{Start}^{Leaf‐out} \{\begin{matrix} 0 if T_{day} < T_{base} \\ \frac{28.4}{1 + {normale}^{- 0.185 (T_{day} - 18.4)}} if T_{day} \geq T_{base} \end{matrix}

where T day is the mean daily temperature from 1 November to the leaf‐out date (including both field and indoor conditions), and T base is the base temperature of 0°C following ref (Wang et al ., 2022).…”

Section: Methodsmentioning

confidence: 99%

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Poleward shifts in the maximum of spring phenological responsiveness of Ginkgo biloba to temperature in China

Wu,

Fu,

Crowther

et al. 2023

New Phytologist

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Summary Global warming is advancing the timing of spring leaf‐out in temperate and boreal plants, affecting biological interactions and global biogeochemical cycles. However, spatial variation in spring phenological responsiveness to climate change within species remains poorly understood. Here, we investigated variation in the responsiveness of spring phenology to temperature (RSP; days to leaf‐out at a given temperature) in 2754 Ginkgo biloba twigs of trees distributed across subtropical and temperate regions in China from 24°N to 44°N. We found a nonlinear effect of mean annual temperature on spatial variation in RSP, with the highest response rate at c. 12°C and lower response rates at warmer or colder temperatures due to declines in winter chilling accumulation. We then predicted the spatial maxima in RSP under current and future climate scenarios, and found that trees are currently most responsive in central China, which corresponds to the species' main distribution area. Under a high‐emission scenario, we predict a 4‐degree latitude shift in the responsiveness maximum toward higher latitudes over the rest of the century. The identification of the nonlinear responsiveness of spring phenology to climate gradients and the spatial shifts in phenological responsiveness expected under climate change represent new mechanistic insights that can inform models of spring phenology and ecosystem functioning.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

GDD = \sum_{Start}^{Leaf‐out} \{\begin{matrix} 0 if T_{day} < T_{base} \\ \frac{28.4}{1 + {normale}^{- 0.185 (T_{day} - 18.4)}} if T_{day} \geq T_{base} \end{matrix}

Section: Methodsmentioning

confidence: 99%

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Poleward shifts in the maximum of spring phenological responsiveness of Ginkgo biloba to temperature in China

Wu,

Fu,

Crowther

et al. 2023

New Phytologist

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“…Other than leaf morphology and thickness, leaf unfolding duration can be influenced by the amount of precipitation, temperature, light, altitude, nutrients etc [34][35][36][37][38][39][40]. For example, leaf unfolding from the bud stage in broad leaved trees might set in earlier at higher temperatures and/or precipitation [34][35][36]. In the same way, a lack of nutrients can delay unfolding [39,40].…”

Section: Unfolding Processes In Peltate Leavesmentioning

confidence: 99%

Leaf unfolding and lamina biomechanics in Syngonium podophyllum and Pilea peperomioides

Modert,

Speck,

Masselter

2024

Bioinspir. Biomim.

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In nature, leaves and their laminae vary in shape, appearance and unfolding behaviour. We investigated peltate leaves of two model species with peltate leaves and highly different morphology (Syngonium podophyllum and Pilea peperomioides) and two distinct unfolding patterns via time-lapse recordings: we observed successive unfolding of leaf halves in S. podophyllum and simultaneous unfolding in P. peperomioides. Furthermore, we gathered relevant morphological and biomechanical data in juvenile (unfolding) and adult (fully unfolded) plants of both species by measuring the thickness and the tensile modulus of both lamina and veins as a measure of their stiffness. In S. podophyllum, lamina and veins stiffen after unfolding, which may facilitate unfolding in the less stiff juvenile lamina. Secondary venation highly contributes to stiffness in the adult lamina of S. podophyllum, while the lamina itself withstands tensile loads best in parallel direction to secondary veins. In contrast, the leaf of P. peperomioides has a higher lamina thickness and small, non-prominent venation and is equally stiff in every region and direction, although, as is the case in S. podophyllum, thickness and stiffness increase during ontogeny of leaves from juvenile to adult. It could be shown that(changes in) lamina thickness and stiffness can be well correlated with the unfolding processes of both model plants, so that we conclude that functional lamina morphology in juvenile and adult leaf stages and the ontogenetic transition while unfolding is highly dependent on biomechanical characteristics, though other factors are also taken into consideration and discussed.

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“…(5) Compared with rural areas, urban vegetation had a longer growing season. Differences between urban and rural phenology are relatively large (Wang et al, 2019b), but how this urban–rural phenology difference responds to climate warming is still unclear and needs further investigation (Wang et al, 2022). In addition to differences in phenology in cities, public health is affected by vegetation phenology such as flowers during was significantly extended in urban than in rural areas.…”

Section: Prospects For Vegetation Phenology Researchmentioning

confidence: 99%

Review of vegetation phenology trends in China in a changing climate

Zhang

Chen

et al. 2022

Progress in Physical Geography: Earth and Environment

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Vegetation phenology is sensitive to climate change and has been defined as the footprint of ongoing climate change. Previous studies have shown that the spatial difference in China’s vegetation phenology varies substantially in both spring and autumn. Here, we reviewed phenological dynamics at the national and the regional scale of China over the period 1982−2020 using a remote sensing-based dataset and meta-analysis from phenological studies in China. We also explored the underlying mechanisms of both spring and autumn phenology and discussed potential phenological studies under future climate conditions. We found that, over the past four decades, the spring phenology advanced at a rate of 0.23 ± 0.47 days/year, while the autumn phenology was delayed at a rate of 0.17 ± 0.46 days/year. This led to an extended vegetation growth season of approximately 5 days per decade. The trends in the spring and autumn phenology were spatially specific in the Northern region, Northwest region, Qinghai–Tibet region, and Southern region: the change in spring phenology was −0.16, −0.46, −0.18, and −0.13 days/year, respectively, while the change in autumn phenology was 0.02, 0.32, 0.09, and 0.28 days/year, respectively. We also explored the dominant climatic drivers of regional phenological changes. We found that temperature was the dominant factor for spring phenology in cold regions, while precipitation, radiation, and temperature co-determined spring phenology in warm regions. The autumn phenology was affected by all three environmental cues but the effect of temperature was larger than that of radiation and precipitation across all regions. In future climate warming conditions, we recommend that studies focus on the phenological feedback mechanisms, such as the climatic and hydrological effects of vegetation changes, and agricultural phenology to investigate its fundamental role in crop productivity, especially under extreme climate events, to ensure national food security and ecological security.

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Climate warming shifts the time interval between flowering and leaf unfolding depending on the warming period

Cited by 7 publications

References 46 publications

Poleward shifts in the maximum of spring phenological responsiveness of Ginkgo biloba to temperature in China

Poleward shifts in the maximum of spring phenological responsiveness of Ginkgo biloba to temperature in China

Leaf unfolding and lamina biomechanics in Syngonium podophyllum and Pilea peperomioides

Review of vegetation phenology trends in China in a changing climate

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