Search

The global mean temperature is increasing due to the increase in greenhouse gases in the atmosphere, but paradoxically, many regions in the mid-latitudes have experienced cold winters recently. Here we analyse multiple observed and modelled datasets to evaluate links between Arctic temperature variation and cold damage in the East Asian terrestrial ecosystem. We find that winter warming over the Barents-Kara Sea has led to simultaneous negative temperature anomalies over most areas in East Asia and negative leaf area index anomalies in southern China where mostly subtropical evergreen forests are growing. In addition to these simultaneous impacts, spring vegetation activity and gross primary productivity were also reduced over evergreen and deciduous trees, and spring phenological dates are delayed. Earth System model simulations reveal that cold damage becomes stronger under greenhouse warming; therefore Arctic warming-induced cold stress should be considered in forest and carbon management strategies.

Autumn phenological variation of temperate and northern ecosystems plays a major but poorly defined role in the global carbon cycle. Constructing robust process-based autumn phenology models is key for improving current ecosystem models to accurately simulate ecosystem productivity and carbon sequestration. In this study, we developed a new process-based autumn phenology model. The model was fitted and validated using 67 leaf coloration and brown-down time series collected for 27 woody and herbaceous species at 18 stations on the Qinghai–Tibetan Plateau from 1981 to 2012. Then, we used the model to analyze the spatial and interspecific differentiation of driving factors of leaf senescence. Moreover, we compared fitting and validation precisions of the new model and previously published models. Results show that leaf senescence processes were triggered by photoperiod shortening in 61.2% of time series but by daily minimum temperature decrease in 38.8% of time series. Photoperiod control of the leaf senescence start occurs predominantly at stations with shorter annual maximum daylength (88.9%), while daily minimum temperature control of the leaf senescence start appears mainly at stations with longer annual maximum daylength (71.0%), especially for the native species. The new model reveals coupling effects of shortened photoperiod and decreased daily minimum temperature on leaf senescence processes. Comparing with the representative existing process-based autumn phenology models, the new model is a more general model and more robust in fitting and predicting leaf coloration and brown-down dates. Our study has provided a new insight on the understanding of leaf senescence mechanisms in winter deciduous trees and herbaceous plants, and significantly improved the ability to predict climate change impacts on vegetation growth and carbon balance in the sensitive biogeographical region of global climate change.

Current process-based models of autumn phenophases are generally based on autumn temperature and/or photoperiod cues. The dependence of autumn phenology on environmental conditions occurring throughout the leafy season has been overlooked. In this study, we incorporated the effect of leafy season temperature and precipitation in process-based models with the aim to improve the modelling of autumn phenology. We tested the ability of three existing and three new autumn phenology models in predicting the occurrence of leaf coloration of four deciduous tree species during 1981–2012 across temperate China. The results show that the models taking the effects of both the leafy season temperature and low precipitation into account performed best over both calibration and validation data. Compared with existing autumn phenological models, the best models predict that the potential delay of autumn phenology in a warmer world is modulated by the impact of leafy season climate on leaf senescence in a complex way: increased leafy season temperature tends to hasten the occurrence of leaf coloration while low leafy season precipitation tends to delay it. Additionally, we tested the hypothesis of a local adaptation of tree phenology through the evaluation of site-specific model parameterizations. Local fittings of the critical temperature sums in all models did not improve the model ability to simulate the occurrence of leaf coloration, which suggests either that local adaptation of leaf senescence process is virtually non-existent across the populations considered or that the genetic variation of leaf coloration traits among populations cannot be detected by our models. Our findings highlighted the importance of leafy season climate in autumn phenology modelling and its possible offset effect in the response of autumn senescence to future warming.

Excessive mitochondrial fission plays a key role in podocyte injury in diabetic kidney disease (DKD), and long noncoding RNAs (lncRNAs) are important in the development and progression of DKD. However, lncRNA regulation of mitochondrial fission in podocytes is poorly understood. Here, we studied lncRNA maternally expressed gene 3 (Meg3) in mitochondrial fission in vivo and in vitro using human podocytes and Meg3 podocyte-specific knockdown mice. Expression of lncRNA Meg3 in STZ-induced diabetic mice was higher, and correlated with the number of podocytes. Excessive mitochondrial fission of podocytes and renal histopathological and physiological parameters were improved in podocyte-specific Meg3 knockdown diabetic mice. Elongated mitochondria with attenuated podocyte damage, as well as mitochondrial translocation of dynamin-related protein 1 (Drp1), were decreased in Meg3 knockout podocytes. By contrast, increased fragmented mitochondria, podocyte injury, and Drp1 expression and phosphorylation were observed in lncRNA Meg3-overexpressing podocytes. Treatment with Mdivi1 significantly blunted more fragmented mitochondria and reduced podocyte injury in lncRNA Meg3-overexpressing podocytes. Finally, fragmented mitochondria and Drp1 mitochondrial translocation induced by high glucose were reduced following treatment with Mdivi1. Our data show that expression of Meg3 in podocytes in both human cells and diabetic mice was higher, which regulates mitochondrial fission and contributes to podocyte injury through increased Drp1 and its translocation to mitochondria.

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.

Climate drivers of plant phenology in the subtropics and tropics are still unclear, which significantly hinders accurate prediction of climate change impacts on vegetation growth and carbon balance in these unique ecoregions. The basic hypothesis of process-based phenology models is that spring tree phenology is regulated by temperature and triggered by chilling temperatures during the dormancy period, followed by forcing temperatures during the growth period. That is, trees require cool temperatures during a chilling period to break endodormancy, and then enter the phase of ecodormancy during which the rate of ontogenetic development increases with increasing air temperature. Therefore, insufficient chilling requirements may slow bud growth and consequently delay budburst. Many studies have shown that chilling requirement is at present sufficient to release bud dormancy fully in temperate regions, and thus forcing temperatures play a dominant role in triggering spring tree phenology. To identify differences in mechanisms of spring tree phenology responses to air temperature between the subtropics/tropics and the temperate zone, and their possible effects on future phenological trends under global warming, we used leaf unfolding and flowering data from a tree species of tropical origin, Melia azedarach, and output daily mean air temperature data from a regional climate model (HadGEM3-RA) for the period 1981–2005 at 42 stations in southeastern China to fit unified forcing and chilling phenology models. Then, we selected optimum models for each phenophase at each station. Moreover, we predicted leafing and flowering dates across the research region over 2021–2100 under global climate warming scenarios. The results show a previously unreported phenological phenomenon: chilling will often be insufficient to break bud dormancy in the northern tropical zone and may become a crucial factor limiting leafing and flowering responses to spring warming. However, chilling will still be sufficient to break bud dormancy in the warm temperate zone, and thus may not limit leafing and flowering responses to spring warming there. Consequently, predicted leafing and flowering dates both will be delayed in the northern tropical zone but will advance in the warm temperate zone from 2021 to 2100. In the subtropical zone, the effect of chilling temperature on spring phenology will be reduced gradually from earlier to later phenophases. Thus, predicted leafing and flowering dates show decreased delaying trends and increased advancing trends from earlier to later phenophases in the subtropical zone. Our findings suggest that insufficient chilling temperature accumulation during the dormancy period may counteract the forcing temperature accumulation during the growth period in the northern tropical zone and parts of the subtropical zone, resulting in delayed leafing and flowering dates.

Examining whether a phenophase occurrence date in the current year affects the same phenophase occurrence date in the following year is crucial for developing cross-year phenological prediction models. Here, we carried out correlation analyses between leaf unfolding start (LUS)/leaf fall end (LFE) dates in the current and following years for four dominant tree species in temperate northern China from 1981 to 2012. Then, we calculated the recurrence intervals of LUS and LFE between two adjacent years for each species. Moreover, we investigated temperature effects on LUS/LFE dates, growing season and non-growing season lengths. Results show that correlation coefficients between LUS/LFE dates in the current and following years are nonsignificant at most stations. The recurrence interval of a phenophase has slight interannual variation and correlates significantly (and negatively) with the phenophase occurrence date of the current year. Further analyses indicate that LUS dates correlate significantly (and negatively) with spring mean temperatures, while LFE dates correlate significantly (and positively) with autumn mean temperatures, but negatively with growing season mean temperatures. In addition, spring mean temperatures can influence growing season length by controlling LUS date but cannot influence the following non-growing season length. Similarly, autumn mean temperatures and growing season mean temperatures can influence the subsequent non-growing season length but cannot influence the growing season length of the following year. Our study highlights that recurrence interval and time restrictions in the effects of seasonal temperatures on phenophase dates are the main environmental causes of nonsignificant correlations between phenophase occurrence dates in the current and following years.

Maternal exposure to airborne particulate matter with aerodynamic diameter

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the landatmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both in situ and satellite observations, we found that vegetation green-up date showed a stronger negative partial correlation with daily minimum temperature (Tmin) than with maximum temperature (Tmax) before the growing season (preseason henceforth). Summer vegetation greenness was strongly positively correlated with summer Tmin, but negatively with Tmax. A 1-K increase in preseason Tmin advanced green-up date by 4 days (P < 0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 20002004 (P < 0.01). In contrast, increases in preseason Tmax did not advance green-up date (P > 0.10) and higher summer Tmax even reduced greenness by 2.6% K−1 (P < 0.05). The stimulating effects of increasing Tmin were likely caused by reduced low temperature constraints, and the apparent negative effects of higher Tmax on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by Tmax. Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon.

We investigated spatial and temporal variations in the accumulated growing degree-days (AGDD) requirement for spring vegetation green-up onset on the Tibetan Plateau (TP) during the rapid warming period of 1998-2012, which is essential for understanding and modeling the spring vegetation phenological responses to climate change. Annual green-up date was determined by using a satellite-derived normalized difference vegetation index. The annual AGDD requirement was then determined as the sum of daily mean air temperatures above 0 degrees C over the dormancy period. Linear regression between the AGDD requirement and year was used to determine its temporal trend. Partial correlation analysis was used to assess factors controlling inter-annual variations in the AGDD requirement. We found the AGDD requirement was significantly different for different vegetation types and showed large spatial variations ranging from a few degrees C-days in cold and wet areas to more than 1000 degrees C-days in warm and dry areas of the TP. Despite the rapid warming and subsequent earlier green-up date, the AGDD requirement did not increase significantly over the period 1998-2012. Interestingly, we found that the inter-annual variations in AGDD requirement were extensively driven by the number of chilling days, while precipitation sum and insolation affected the AGDD requirement in limited areas. Although the winter warming reduced chilling accumulation on the TP, the AGDD requirement for vegetation green-up onset did not necessarily increase over 1998-2012, being insensitive to decline in the chilling accumulation. This suggested that the chilling requirement to break vegetation dormancy might be still fulfilled. In other words, the winter warming might not substantially affect the vegetation green-up process, since the reduction in chilling accumulation may not affect the dormancy break. However, the negative temporal correlation between the AGDD requirement and number of chilling days indicates that continued future warming may lead to a deficiency in chilling and thus an increase in AGDD requirement. (C) 2016 Elsevier B.V. All rights reserved.

Using spatial phenology model-based Ulmus pumila leaf unfolding and leaf fall data at 8 km × 8 km grids, we analysed spatial relationships between ground-based and satellite-derived growing season beginning and end dates during the period 2001–2005 and examined climatic controls on spatial correlations between ground-based and satellite-derived growing seasons. The results show that the regional mean satellite-derived growing season clearly started earlier and terminated slightly later than the regional mean ground-based growing season. Meanwhile, spatial patterns of satellite-derived growing season beginning and end dates correlate positively with spatial patterns of ground-based growing season beginning and end dates in each year (p < 0.001). Interannual variation in the difference of the slope of the spatial regression between ground-based/satellite-derived growing season beginning date and February–April temperature controls interannual variation of the spatial correlation coefficient between ground-b...

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.

From the perspectives of natural landscape dynamics, plant phenology is the study of the timing (and quantity) of annually recurring plant growth and reproductive phenomena, as well as the drivers of these events associated with endogenous and exogenous forces. Conventional plant phenology usually serves as time steps and markers of vegetation growth and reproductive processes within a year and among different years, while modern plant phenology can serve as a key link between climate change and biogeochemical cycles at seasonal and interannual scales.

Plant phenological observations show that occurrence dates of plant growth and reproduction stages are different at different locations, which is mainly a macroscopic and integrative reflection of climatic spatial heterogeneity. Early studies on spatial differences of plant phenology focused on geographical dependence of phenological spatial differences . Typical geographical models of plant phenology were shown as multiple linear regression equations between multi-year mean phenological occurrence dates at individual sites and geo-location parameters (latitude, longitude, and elevation). More recent studies attempt to reveal the relationship between phenological and climatic spatial patterns. Because air temperature is the most important factor influencing spatial variation of plant phenology, multi-year mean monthly temperatures at individual sites (replacing geo-location parameters) have be used as the independent variable for fitting spatial patterns of plant phenological occurrence dates.

Plant phenological observations show that plant growth and reproduction obey a certain temporal rhythmicity, which is a macroscopic and integrative reflection of local and regional natural landscape dynamics . The most obvious temporal rhythmicities of plant phenology are displayed as sequential and correlative rhythm , circannual rhythm , multi-year rhythm , circadian rhythm , and overlap rhythm . Temporal rhythmicity of plant phenology is mainly attributed to climatic rhythmicity, photoperiod, and response properties of phenological phenomena to weather and climate.

Daily mean air temperature-based spatial phenology models were fitted and validated using Ulmus pumila first leaf unfolding and leaf fall end data at 46 stations within China’s temperate zone from 1986 to 2005. Results show that spatial patterns of first leaf unfolding and leaf fall end dates were obviously influenced by spatial patterns of daily mean air temperatures during the optimum spring and autumn length period, respectively. A higher location-specific multi-year mean spring and autumn temperature resulted in an earlier location-specific multi-year mean first leaf unfolding date and a later leaf fall end date. On average, a 1 °C spatial shift in multi-year mean spring and autumn temperatures may cause a spatial shift of −3.1 days and 2.6 days in multi-year mean first leaf unfolding and leaf fall end dates, respectively. Similar spatial relationships were also detected between daily mean temperature and phenological occurrence date in each year. The regression equations indicate that a 1 °C spatial shift in yearly mean spring and autumn temperatures may induce a spatial shift between −4.28 and −2.75 days in yearly first leaf unfolding date, and between 2.17 and 3.16 days in yearly leaf fall end date. Error estimation confirmed the reliability of multi-year mean and yearly spatial phenology models in simulating and predicting spatial patterns of Ulmus pumila first leaf unfolding and leaf fall end dates. Further analysis showed that a 1 °C spatial shift in mean spring temperature in warmer years may induce a larger spatial shift in first leaf unfolding date than that in colder years. Thus, future climate warming may enhance sensitivity of the spatial response of first leaf unfolding to temperature.

We used Ulmus pumila leaf unfolding and leaf fall data collected at 46 stations during the 1986–2005 period to construct and validate daily temperature-based spatial phenology models. These models allowed simulation of the 20-year mean and yearly spatial patterns of U. pumila growing season beginning and end dates. This work was undertaken to explore the ecological mechanisms driving tree phenology spatial patterns and examine tree phenology spatial responses to temperature across China's temperate zone. The results show that spatial patterns of daily temperatures within the optimum spring and autumn length periods control spatial patterns of growing season beginning and end dates, respectively. Regarding 20-year mean growing season modeling, mean growing season beginning date correlates negatively with mean daily temperature within the optimum spring length period at the 46 stations. The mean spring spatial phenology model explained 90% of beginning date variance (P

Using Ulmus pumila (Siberian Elm) leaf unfolding and leaf fall phenological data from 46 stations in the temperate zone of China for the period 1986-2005, we detected linear trends in both start and end dates and length of the growing season. Moreover, we defined the optimum length period during which daily mean temperature affects the growing season start and end dates most markedly at each station in order to more precisely and rationally identify responses of the growing season to temperature. On average, the growing season start date advanced significantly at a rate of -4.0 days per decade, whereas the growing season end date was delayed significantly at a rate of 2.2 days per decade and the growing season length was prolonged significantly at a rate of 6.5 days per decade across the temperate zone of China. Thus, the growing season extension was induced mainly by the advancement of the start date. At individual stations, linear trends of the start date correlate negatively with linear trends of spring temperature during the optimum length period, namely, the quicker the spring temperature increased at a station, the quicker the start date advanced. With respect to growing season response to interannual temperature variation, a 1°C increase in spring temperature during the optimum length period may induce an advancement of 2.8 days in the start date of the growing season, whereas a 1°C increase in autumn temperature during the optimum length period may cause a delay of 2.1 days in the end date of the growing season, and a 1°C increase in annual mean temperature may result in a lengthening of the growing season of 9 days across the temperate zone of China. Therefore, the response of the start date to temperature is more sensitive than the response of the end date. At individual stations, the sensitivity of growing season response to temperature depends obviously on local thermal conditions, namely, either the negative response of the start date or the positive response of the end date and growing season length to temperature was stronger at warmer locations than at colder locations. Thus, future regional climate warming may enhance the sensitivity of plant phenological response to temperature, especially in colder regions.

Zinc has been implicated to have a protective role against heart malformations during fetal development. Metallothionein 1 (MT-1) and zinc transporter 1 (ZnT-1) are two major metabolic factors that are associated with zinc metabolism. The present work aimed to investigate the association of placental MT-1 and ZnT-1 expressions with fetal heart malformations resulting from maternal zinc deficiency. Sprague–Dawley female rats were randomly divided into five groups of extremely low-zinc, low-zinc, moderately low-zinc, marginally low-zinc and normal zinc (n = 9–12), and were fed diets with controlled zinc content at 1.0 ± 0.3, 8.4 ± 1.8, 15.4 ± 2.8, 22.4 ± 4.1 and 29.4 ± 5.3 [mean ± standard deviation (SD)] mg of zinc/kg, respectively, from day 25 of preconception until day 19 of gestation. The female rats were bred, their fetuses were harvested at day 19 of gestation after killing the dams, and fetal hearts were morphologically examined. Zinc concentration and alkaline phosphatase (ALP) activity in maternal venous blood sera were tested, and MT-1 and ZnT-1 mRNA expressions in the placenta were assayed. Zinc concentrations and ALP activities in the blood were low in all zinc-deficient diet groups in a dose-dependent fashion. The incidences of heart malformations were increased, and the levels of placental MT-1 and ZnT-1 mRNA expressions were decreased in the extremely low-zinc, low-zinc and moderately low-zinc groups compared with the normal zinc group. Specifically, mRNA levels of placental MT-1 or ZnT-1 were significantly decreased and were lower than the specific threshold values in the fetuses with heart malformations but not in the fetuses without heart malformations in all the groups. These data indicate that maternal zinc deficiency resulted in an elevated incidence of fetal heart malformations, which was associated with significant decreases in placental MT-1 and ZnT-1 mRNA expressions to the levels below the threshold values that may be a crucial factor to determine the presence of fetal heart malformations.

Evidence suggests that prenatal exposure to air pollution affects the ontogeny and development of the fetal immune system. The aim of this study was to investigate the effect of maternal exposure to airborne particulate matter (PM) on immune function in postnatal offspring. Pregnant female ICR mice were intralaryngopharyngeally administered with 30 μl of phosphate buffered solution (the control group) or resuspended PM of Standard Reference Material 1649a at 0.09 (low), 0.28 (medium), 1.85 (high) or 6.92 (overdose) μg/μl once every three days from day 0 to 18 of pregnancy (n = 8–10). Offspring were sacrificed on postnatal day 30. Interleukin-4 and interferon-γ levels in plasma and splenocytes, splenic lymphocyte proliferation, and expressions of GATA-3 and T-bet mRNA in the spleen were tested. The spleen and thymus were histopathologically examined. The offspring of the medium, high and overdose PM-exposed dams showed significantly suppressed splenocyte proliferation. Decreased interferon-γ and increased interleukin-4 levels in the blood and splenocytes, and lowered T-bet and elevated GATA-3 mRNA expressions were found in the spleen in the medium, high and overdose groups when compared with the control or low dose group (P < 0.05). Histopathology revealed prominent tissue damage in the spleen and thymus in the overdose group. These results suggest that exposure of pregnant mice to PM modulates the fetal immune system, resulting in postnatal immune dysfunction by exacerbation of Thl/Th2 deviation. This deviation is associated with altered T-bet and GATA-3 gene expressions.

Using first leaf unfolding data of Salix matsudana, Populus simonii, Ulmus pumila, and Prunus armeniaca, and daily mean temperature data during the 1981–2005 period at 136 stations in northern China, we fitted unified forcing and chilling phenology models and selected optimum models for each species at each station. Then, we examined performances of each optimum local species-specific model in predicting leaf unfolding dates at all external stations within the corresponding climate region and selected 16 local species-specific models with maximum effective predictions as the regional unified models in different climate regions. Furthermore, we validated the regional unified models using leaf unfolding and daily mean temperature data beyond the time period of model fitting. Finally, we substituted gridded daily mean temperature data into the regional unified models, and reconstructed spatial patterns of leaf unfolding dates of the four tree species across northern China during 1960–2009. At local scales, the unified forcing model shows higher simulation efficiency at 83% of data sets, whereas the unified chilling model indicates higher simulation efficiency at 17% of data sets. Thus, winter temperature increase so far has not yet significantly influenced dormancy and consequent leaf development of deciduous trees in most parts of northern China. Spatial and temporal validation confirmed capability and reliability of regional unified species-specific models in predicting leaf unfolding dates in northern China. Reconstructed leaf unfolding dates of the four tree species show significant advancements by 1.4–1.6 days per decade during 1960–2009 across northern China, which are stronger for the earlier than the later leaf unfolding species. Our findings suggest that the principal characteristics of plant phenology and phenological responses to climate change at regional scales can be captured by phenological and climatic data sets at a few representative locations.

Allelopathy arises from the release of chemicals by one plant species that affect other species in its vicinity, usually to their detriment. Allelopathic effects have been demonstrated to be limiting factors for species distributions and ecological processes in some natural or agricultural communities. Based on the biphasic hormetic responses of plants to allelochemicals, ecological-limiting-factor models were introduced into the An-Johnson-Lovett hormesis model to improve modelling the phenomenon of allelopathic hormesis and to better reflect the nature of allelopathy as a limiting factor in ecological processes. Outcomes of the models have been compared for several sets of experimental data from the literature and good agreement between the models and data was observed, which indicates that the new models give some insight into the ecological mechanisms involved and may provide more options for modelling the allelopathic phenomenon as well as platforms for further research on plant allelopathic hormesis.

Seasonal biome dynamics are controlled by recurrent variations of environmental conditions, especially climate. Therefore, in temperate areas with distinct climatic rhythmicity, seasonal biome features are rich and colorful. The most obvious natural stages during a year are growing season and rest period. Further, several characteristic sub-stages can be identified within growing season and rest period through careful observation. Because plant phenological events are integrative indicators of seasonal changes, using occurrence dates of phenophases to determine seasons (especially the growing season) is an effective way to reveal the overall characteristics of nature’s seasonality. This information is useful for doing agricultural tasks in the right season, making seasonal landscape designs, preventing plant diseases and insect pests, directing sightseeing (Yang and Chen 1980), and validating remote sensing phenology (Chen et al. 2000).