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1.
Sci Total Environ ; 934: 173280, 2024 Jul 15.
Article in English | MEDLINE | ID: mdl-38768721

ABSTRACT

Simulating the timing of leaf fall in large scale is crucial for accurate estimation of ecosystem carbon sequestration. However, the limited understanding of leaf senescence mechanisms often impedes the accuracy of simulation and prediction. In this study, we employed the advanced process-based models to fit remote sensing-derived end dates of the growing season (EOS) across deciduous broadleaf forests in the Northern Hemisphere, and revealed the spatial pattern associated with two leaf senescence pathways (i.e., either photoperiod- or temperature- initiated leaf senescence) and their potential effects on EOS prediction. The results show that the pixel-specific optimum models effectively fitted all EOS time series. Leaf senescence in 67.6 % and 32.4 % of pixels was initiated by shortening daylength and declining temperature, respectively. Shortening daylength triggered leaf senescence occurs mainly in areas with shorter summer daylength and/or warmer autumns, whereas declining temperature induced leaf senescence appears primarily in areas with longer summer daylength and/or colder autumns. The strong dependence of leaf senescence initiation cues on local temperature conditions implies that the ongoing increase in autumn temperature has the potential to alter the leaf senescence initiation, shifting from temperature cues to photoperiod signals. This shift would occur in 26.2-49.6 % of the areas where leaf senescence is initiated by declining temperature under RCP 4.5 and 8.5 scenarios, while forest areas where leaf senescence is induced by shortening daylength may expand northward. The overall delaying of the currently predicted EOS would therefore slow down by 4.5-10.3 % under the two warming scenarios. This implies that the adaptive nature of plants will reduce the overestimation of changes in carbon exchange capacity between ecosystems and atmosphere. Our study offers novel insights into understanding the mechanism of leaf senescence and improving the estimation of autumn phenology and ecosystem carbon balance in the deciduous broadleaf forests.


Subject(s)
Forests , Plant Leaves , Seasons , Temperature , Plant Leaves/physiology , Plant Senescence , Trees/physiology , Remote Sensing Technology , Carbon Sequestration , Photoperiod
2.
Int J Biometeorol ; 67(9): 1409-1421, 2023 Sep.
Article in English | MEDLINE | ID: mdl-37479847

ABSTRACT

Evaluating the interactions between cold requirements for leaf coloration and environmental cues is crucial for understanding the mechanisms of leaf senescence and accurately predicting autumn phenology. Based on remote sensing-derived and ground-observed leaf coloration dates for deciduous broadleaf forests during 1981-2014, we determined location-specific cold requirements for autumn leaf coloration and assessed their spatiotemporal changes. Then, we revealed the major environmental cues of cold requirements and their spatial differentiation. Results show that cold requirements have nonsignificant trends during the past decades at 57.9% of pixels. The interannual variation of cold requirements was mainly influenced by growing-season accumulated temperature (GDDgs) at 35.8% of pixels and accumulated growing season index (AGSI) at 23.2% of pixels, but less affected by leaf unfolding and low precipitation index (LPI). The increase in GDDgs or AGSI may decrease cold requirements, and vice versa. The spatial differentiations of the effects of GDDgs and AGSI depend highly on local summer temperature among climatic classifications with similar humidity conditions. Specifically, the effects of GDDgs on cold requirements concentrated in humid regions with warmer summers, while that of AGSI mainly occurred in humid and winter dry regions with cooler summers. Higher summer temperatures would strengthen the effects of GDDgs and reduce the effects of AGSI on cold requirements. These findings deepen the understanding of the influences of environmental factors on leaf senescence progress and suggest that the shifts of factors affecting cold requirements under global warming may enlarge the uncertainty in predicting autumn leaf coloration dates.


Subject(s)
Cues , Trees , Forests , Seasons , Temperature , Plant Leaves , Climate Change
3.
Front Plant Sci ; 14: 1327509, 2023.
Article in English | MEDLINE | ID: mdl-38273945

ABSTRACT

Climate warming has induced significant shifts in spring phenology over both temperate and boreal forests. The timing of bud growth resuming from dormancy is crucial for predicting spring phenology. However, the mechanisms by which environmental cues, other than chilling accumulation, initiate bud growth remains unclear. By constructing a revised process-based spring phenology model incorporating photoperiod and temperature triggers of bud growth, we simulated the first leaf unfolding and first flowering dates of four deciduous forest trees during 1981-2014 at 102 stations across China's monsoon regions. Then, we revealed spatial patterns of the two triggers. Moreover, we compared fitting precision and robustness of the revised model with three mainstream models. Results show that the revised models can effectively simulate all spring phenology time series. Growth initiation of foliar and floral buds was induced by photoperiod lengthening in 80.8% and 77.7% of time series, and by temperature increasing in remaining 19.2% and 22.3% of time series, respectively. The proportions of time series with photoperiod- and temperature-initiated bud growth significantly increase and decrease from northern to southern climatic zones, respectively. Chilling exposure controls the predominant bud growth triggers in different climate zones. Specifically, in regions with long and severe winters where chilling requirement is easily fulfilled, rising temperature in spring alleviates the cold constraint and initiate bud growth. Conversely, in regions with short and mild winters, prolonged daylength in spring compensates the lack of chilling exposure to initiate bud growth. These findings suggest that photoperiod may limit spring phenology response to temperature in low-latitudes. Overall, our model slightly outperforms other models in terms of efficiency, accuracy, and robustness in modeling leaf unfolding and flowering dates. Therefore, this study deepens our understanding of the mechanisms of spring phenology, and improves the predicting capability of spring phenology models in the face of ongoing global warming.

4.
Front Plant Sci ; 13: 844971, 2022.
Article in English | MEDLINE | ID: mdl-35392512

ABSTRACT

The phenology of alpine grassland on the Qinghai-Tibet Plateau (QTP) is critical to regional climate change through climate-vegetation feedback. Although many studies have examined QTP vegetation dynamics and their climate sensitivities, the interspecific difference in the phenology response to climate change between alpine species is poorly understood. Here, we used a 30-year (1989-2018) record of in situ phenological observation for five typical alpine herbs (Elymus nutans, Kobresia pygmaea, Plantago asiatica, Puccinellia tenuiflora, and Scirpus distigmaticus) and associated climatic records at Henan Station in the eastern QTP to examine the species-level difference in spring and autumn phenology and then quantify their climate sensitivities. Our results show that with significantly warming, the green-up dates of herbs were insignificantly shifted, while the brown-off dates in four out of the five herbs were significantly delayed. Meanwhile, the interspecific difference in brown-off dates significantly increased at a rate of 0.62 days/annual from 1989 to 2016, which was three times larger than that in green-up dates (0.20 days/annual). These diverse rates were attributed to the different climate controls on spring and autumn phenology. In particular, green-up dates in most herbs were sensitive to mean surface temperature, while brown-off dates were sensitive to the night surface temperature. Furthermore, brown-off dates are less sensitive to the warming in high ecological niche (with higher herb height and aboveground biomass) herbs than low niche herbs (with lower herb height and aboveground biomass). The increased phenology interspecific difference highlights the complex responses of herbs to future climate change even under the same alpine environment and indicates a potential alternation in the plants community of alpine QTP, which may further influence the regional climate-vegetation feedback.

5.
Int J Biometeorol ; 64(11): 1911-1922, 2020 Nov.
Article in English | MEDLINE | ID: mdl-32740667

ABSTRACT

Using leaf area index (LAI) data from 1981 to 2014 in the tropical moist forest eco-zone of South America, we extracted start (SOS) and end (EOS) dates of the active growing season in forest and savanna at each pixel. Then, we detected spatiotemporal characteristics of SOS and EOS in the two vegetation types. Moreover, we analyzed relationships between interannual variations of SOS/EOS and climatic factors, and simulated SOS/EOS time series based on preceding mean air temperature and accumulated rainfall. Results show that mean SOS and EOS ranged from 260 to 330 day of year (DOY) and from 150 to 260 DOY across the study region, respectively. From 1981 to 2014, SOS advancement is more extensive than SOS delay, while EOS advancement and delay are similarly extensive. For most pixels of forest and savanna in tropical moist forest eco-zone, preceding rainfall correlates predominantly negatively with SOS but positively with EOS, while the relationship between preceding temperature and phenophases is location-specific. In addition, preceding rainfall is more extensive than preceding temperature in simulating SOS, while both preceding rainfall and temperature play an important role for simulating EOS. This study highlights the reliability of using LAI data for long-term phenological analysis in the tropical moist forest eco-zone.


Subject(s)
Forests , Reproducibility of Results , Seasons , South America , Temperature
6.
Glob Chang Biol ; 24(8): 3537-3545, 2018 08.
Article in English | MEDLINE | ID: mdl-29460318

ABSTRACT

Autumn phenology remains a relatively neglected aspect in climate change research, which hinders an accurate assessment of the global carbon cycle and its sensitivity to climate change. Leaf coloration, a key indicator of the growing season end, is thought to be triggered mainly by high or low temperature and drought. However, how the control of leaf coloration is split between temperature and drought is not known for many species. Moreover, whether growing season and autumn temperatures interact in influencing the timing of leaf coloration is not clear. Here, we revealed major climate drivers of leaf coloration dates and their interactions using 154 phenological datasets for four winter deciduous tree species at 89 stations, and the corresponding daily mean/minimum air temperature and precipitation data across China's temperate zone from 1981 to 2012. Results show that temperature is more decisive than drought in causing leaf coloration, and the growing season mean temperature plays a more important role than the autumn mean minimum temperature. Higher growing season temperature and lower autumn minimum temperature would induce earlier leaf coloration date. Moreover, the mean temperature over the growing season correlates positively with the autumn minimum temperature. This implies that growing season mean temperature may offset the requirement of autumn minimum temperature in triggering leaf coloration. Our findings deepen the understanding of leaf coloration mechanisms in winter deciduous trees and suggest that leaf life-span control depended on growing season mean temperature and autumn low temperature control and their interaction are major environmental cues. In the context of climate change, whether leaf coloration date advances or is delayed may depend on intensity of the offset effect of growing season temperature on autumn low temperature.


Subject(s)
Climate Change , Droughts , Temperature , Trees/physiology , China , Color , Pigmentation , Plant Leaves/physiology , Populus/physiology , Robinia/physiology , Salix/physiology , Seasons , Ulmus/physiology
7.
Int J Biometeorol ; 61(10): 1733-1748, 2017 Oct.
Article in English | MEDLINE | ID: mdl-28466416

ABSTRACT

Using woody plant phenological data in the Beijing Botanical Garden from 1979 to 2013, we revealed three levels of phenology rhythms and examined their coherence with temperature rhythms. First, the sequential and correlative rhythm shows that occurrence dates of various phenological events obey a certain time sequence within a year and synchronously advance or postpone among years. The positive correlation between spring phenophase dates is much stronger than that between autumn phenophase dates and attenuates as the time interval between two spring phenophases increases. This phenological rhythm can be explained by positive correlation between above 0 °C mean temperatures corresponding to different phenophase dates. Second, the circannual rhythm indicates that recurrence interval of a phenophase in the same species in two adjacent years is about 365 days, which can be explained by the 365-day recurrence interval in the first and last dates of threshold temperatures. Moreover, an earlier phenophase date in the current year may lead to a later phenophase date in the next year through extending recurrence interval. Thus, the plant phenology sequential and correlative rhythm and circannual rhythm are interacted, which mirrors the interaction between seasonal variation and annual periodicity of temperature. Finally, the multi-year rhythm implies that phenophase dates display quasi-periodicity more than 1 year. The same 12-year periodicity in phenophase and threshold temperature dates confirmed temperature controls of the phenology multi-year rhythm. Our findings provide new perspectives for examining phenological response to climate change and developing comprehensive phenology models considering temporal coherence of phenological and climatic rhythmicity.


Subject(s)
Magnoliopsida/growth & development , Beijing , Climate , Seasons , Temperature
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