Search

Wheat is one of the most common and productive crops in the world, and the growth and production of wheat are sensitive to climate change. Climate change affects wheat phenology by influencing sowing/maturity dates and the duration of growing stages, and ultimately affects the grain yield. Reliable prediction of changes in wheat yield is significant for maintaining global food security. However, studies addressing the potential impact of crop phenology changes on grain yield are rarely reported, which is a big challenge. Using the CERES-Wheat model and first-order differential equation models, we quantified the impact of future climate change on wheat phenology and grain yield for two periods (P1: 2011–2040; P2: 2041–2070) under three representative concentration pathways (RCP2.6, RCP4.5, RCP8.5) in China's two main wheat-growing areas (Northwest Spring Wheat-Growing Area (NWSWA) and Huang–Huai–Hai Winter Wheat-Growing Area (HHWWA)); the baseline period was 1981–2010. Accumulated thermal time during the whole growing period (WGP) tends to significantly increase in NWSWA and HHWWA under all RCPs and periods. This rising accumulated thermal time will reduce the time to anthesis and maturity and shorten the vegetative growing period (VGP), reproductive growing period (RGP), and the WGP. In P2, spring wheat grain yield is projected to diminish by a regional average of 2.67% for RCP2.6, 4.07% for RCP4.5, and 5.66% for RCP8.5, which is dominated by the lower accumulated solar radiation during the VGP in NWSWA. Additionally, for the winter wheat grain yield in HHWWA in P2, its grain yield reduction is projected to decline by 4.8% (RCP2.6), 7.9% (RCP4.5), and 9.8% (RCP8.5), which is caused by increasing accumulated thermal time in the VGP. These results suggest that breeding high-temperature-tolerant varieties with high calorie requirements is an adaptive strategy to mitigate the negative impact of climate change on wheat yield in the study areas.

A warmer climate has caused more extreme climate events like the heatwave or extreme precipitation, which has led to a large number of lives and economic losses. In this study, we adopt historical daily precipitation from rainfall estimates on a gridded network (REGEN) and future daily projections from 10 general circulation models (GCMs) to analyze the potential risks of extreme precipitation due to changes in the magnitude and frequency. We calculate the 10-year and 100-year return levels by fitting the partial duration series (PDS) data with the generalized Pareto (GP) distribution. The potential risks are quantified in two terms: by the ratio of the magnitude to the threshold and by the exceedance frequency comparing to the theoretical value. The results show that in the future, about 46% of the world may suffer from mid or high risk of change in extreme precipitation. Most regions show higher risk due to the increased frequency of extreme precipitation events under the RCP8.5 scenario. The high risk of humid regions mainly appears under the RCP8.5 scenario and is mainly driven by frequency change, while that of arid regions appears under both the scenarios and is driven by both the frequency and magnitude change. The tropical rainforest climate areas of South America (SA (N)), the tropical savanna or tropical wet monsoon and tropical dry areas of South Asia (SA), and the subarctic climate areas of Northern Asia (NOA) may suffer more risks from the view of both magnitude and frequency changes of extreme precipitation.

Climate warming has advanced the spring phenology of many plant species by accelerating heat accumulation. However, delayed phenophases due to insufficient chilling have also been reported. Based on phenological observation data (1963-2010), we compared the effects of preseason chill and heat accumulation on leaf unfolding dates of four deciduous woody species (Lagerstroemia indica, Robinia pseudoacacia, Sophora japonica, and Ulmus pumila) in temperate and subtropical regions of China. Daily chill and heat accumulation were calculated by two chilling models (the Positive Utah Model and the Dynamic Model) and the Growing Degree Hour (GDH) Model. We determined the temporal trends in chill and heat accumulations for leaf unfolding of the four species. The results showed that there were shorter chilling periods in the subtropics than in temperate sites because the chilling period typically started later and ended earlier. There was no significant difference in the length of the forcing period in the different regions. The chilling requirements for leaf unfolding were higher in temperate regions (1344.9-1798.9 chilling units (CU) or 64.7-79.4 chilling portions (CP)) than in the subtropics (1145.9-1828.1 CU or 47.9-75.2 CP). Plants in the subtropics needed higher forcing temperatures (4135.8-10084.8 GDH) than those in temperate regions (3292.0-8383.6 GDH). The earlier-leafing species (e.g., U. pumila) had a lower heat requirement for leaf unfolding than the later-leafing species (e.g., L. indica). A significant increase in heat accumulation was found at all sites except Guiyang, while chill accumulation only increased in Beijing.

Climate change could affect botanical tourism by altering the plant phenology (e.g., flowering and leaf coloring date) and the physical comfort of tourists. To date, few studies have simultaneously considered the influence of plant phenology and physical comfort on the travel suitability of botanical tourism. Taking Beijing as an example, this study used phenological data of 73 species from 1963 to 2017 to construct a phenological ornamental index (POI) according to the flowering and leaf coloring date of ornamental plant. The climate comfort index (CCI) of tourism was calculated by using meteorological data of the corresponding periods. Finally, the travel suitability index (TSI) was constructed by integrating the two indices (POI and CCI). The POI showed that the best period for spring flower viewing was from April 4 to May 10, while the best period for autumn leaves viewing was from October 11 to November 6 on average. According to the variation of the CCI within the year, the most comfortable period for spring tourism was matched with the best period for spring flower viewing (April 4 to June 1), but the most comfortable period for autumn tourism (September 4 to October 19) was earlier than the best period for autumn leaves viewing. The TSI indicated that the best periods for spring and autumn botanical tourism were April 7 to May 10 and October 10 to November 7, respectively. Based on the climate data under different scenarios (representative concentration pathways 4.5 and 8.5), we simulated the climate and phenological suitability for botanical tourism in the next thirty years. The results showed that the best period for spring botanical tourism during 2040–2050 was earlier and the period for autumn botanical tourism was later than that in the past 55 years. Meanwhile, the duration would shorten by 2–7 days for both seasons. This study provided a reference for assessing the impact of global climate change on the best season of botanical tourism.

Intended nationally determined contributions (INDCs) are a new strategy for mitigating climate change. Many international organizations and scholars have assessed the possibility of holding the increase in global average temperature to well below 2°C based on INDCs. Although the conclusions of these assessments are consistent, there are still large differences among the assessment results. For example, the global greenhouse gas emissions in 2030 estimated by INDCs are between 47.1–66.5 GtCO2 eq, and the temperature increase at the end of the 21st century estimated by INDCs is between 2.4–4.0°C; the inconsistency represented by these ranges is not conducive to an accurate assessment of the contributions of the current INDCs to global warming mitigation or to the further development of emissions reduction programs. By summarizing the existing studies, we found that the main reasons for the differences in estimates of global greenhouse gas emissions in 2030 made using INDCs are as follows: (1) The studies interpreted INDCs differently, which is attributable to three reasons: The studies (a) made different assumptions for the unquantifiable INDCs; (b) ignored or used different methods to estimate the emissions not covered by INDCs; and (c) used different amounts of INDCs because the studies were performed at different times. (2) The studies used different databases that include different greenhouse gases, accounting methods and data sources to estimate historical greenhouse gas emissions. (3) The studies used different methods for estimating greenhouse gas emissions and removals related to land use, land-use change and forestry (LULUCF). (4) The studies used different values of the global warming potential. Additionally, the main reasons for the differences in the predictions of the temperature increase at the end of the 21st century based on INDCs are as follows: (1) Differences in the estimations of greenhouse gas emissions in 2030 based on INDCs and (2) different methods of extrapolating global greenhouse gas emissions to 2100. There are three main extrapolation methods: one is to maintain the net present value of the carbon price in 2030 and then extrapolate the greenhouse gas emissions to 2100; another is to maintain the decarbonization rate of a certain period of history and then extrapolate the greenhouse gas emissions to 2100; the third is to match the emissions reduction scenario with the current INDC emissions reduction scenario from the IPCC AR5 scenario database and then use the matching emissions reduction scenario as the current INDC emissions reduction scenario. The use of different methods of extrapolating carbon emissions is one of the main reasons for the differences in the prediction results. (3) Differences in the methods for predicting the effects of greenhouse gas emissions on temperature. Statistical methods and simulation methods are the two main prediction methods; they use different calculation methods, which led to the difference in the prediction results. Therefore, the following points are worth noting: (1) Most importantly, to the extent possible, countries should submit absolute emissions reduction targets as much as possible; nonquantifiable INDCs without detailed methods descriptions and data introductions should not be submitted; (2) authorities should recommend certain data sets that are the most suitable for INDC accounting; (3) a global warming potential should be designated to avoid differences in greenhouse gas estimates due to the use of different criteria; and (4) to the extent possible, future research should adopt simulation methods for predicting the impact of global greenhouse gas emissions on temperature.

Winter temperature-related chilling and spring temperature-related forcing are two major environmental cues shaping the leaf-out date of temperate species. To what degree insufficient chilling caused by winter warming would slow phenological responses to spring warming remains unclear. Using 27,071 time series of leaf-out dates for 16 tree species in Europe, we constructed a phenological model based on the linear or exponential function between the chilling accumulation (CA) and forcing requirements (FR) of leaf-out. We further used the phenological model to quantify the relative contributions of chilling and forcing on past and future spring phenological change. The results showed that the delaying effect of decreased chilling on the leaf-out date was prevalent in natural conditions, as more than 99% of time series exhibited a negative relationship between CA and FR. The reduction in chilling linked to winter warming from 1951 to 2014 could offset about one half of the spring phenological advance caused by the increase in forcing. In future warming scenarios, if the same model is used and a linear, stable correlation between CA and FR is assumed, declining chilling will continuously offset the advance of leaf-out to a similar degree. Our study stresses the importance of assessing the antagonistic effects of winter and spring warming on leaf-out phenology., This work was funded by the National Key R&D Program of China (Grant No. 2018YFA0606102), National Natural Science Foundation of China (Grant No. 41871032, 42125101), Youth Innovation Promotion Association, CAS (Grant No. 2018070), and Program for “Kezhen” Excellent Talents in IGSNRR, CAS (Grant No. 2018RC101).

The Ancient Silk Road has a history of more than 2000 years and gave birth to the diversities of culture between East and West. Climate change may have played a crucial role in this process and in the flourishing and decline of civilizations. In this work, high-resolution temperature reconstructions covering more than 1000 years along the Ancient Silk Road are reviewed, and the main characteristics of temperature and hydroclimatic changes are summarized. Four warm stages occurred that included the 1st–3rd centuries, the late 7th century to the early 11th century, the mid-12th century to the mid-13th century, and since the 20th century, and three cold stages, including the 4th century to the early 7th century, the middle of the 11th century to the early 12th century, and the end of the 13th century to the mid-19th century, occurred. Within these various stages, regional differences existed in amplitudes and starting–ending years of the cold/warm phases. Wetness and dryness variabilities during the Medieval Climate Anomaly (MCA) were greater than during the Little Ice Age in Northwestern China. The climate was dry during the MCA in Central Asia, South Scandinavia, and North-central Europe. In addition, the climate backgrounds of several famous kingdoms flowering and social events that flourished during these times, such as the Roman Empire, the Loulan Kingdom, the Tibetan Kingdom, and the three unprecedented Mongol westward conquests, are discussed.

Changes in crop phenology may reflect crop responses and adaptation to climate change. In this study, we used observational data (1981-2010) of maize (Zea mays L.) phenology from agricultural meteorological stations in the major maize-growing regions of China to examine spatiotemporal changes in the phenologies and growth periods and associated sensitivities to changes in major climatic factors. The results showed that, during the study period, sowing, tasseling, and maturity dates for maize were delayed in most maize growth regions. The lengths of vegetative growth period (VGP, from emergence to tasseling) were increased in spring and spring-summer maize growth regions and decreased in summer maize growth regions; the lengths of the maize reproductive growth period (RGP, from tasseling to maturity) and whole growth period (WGP, from emergence to maturity) were mostly extended (except NWMR_SU). Overall, sensitivity of maize VGP, RGP, and WGP was negatively related to average temperature (P < 0.01) and positively related to precipitation and sunshine hours (P < 0.01); there were variations in sensitivity among regions and data station locations. Precipitation was a driver of growth period length in the northwest inland maize region, whereas mean temperature and sunshine hours were drivers in the southwest hilly region.

Since the mid-19th century, the global atmospheric CO2 concentration (ACC) has increased dramatically due to the burning of fossil fuels. Because of unequal population growth and economic development among regions, the ACC increases possess strong spatial variability. Particularly, the increase in ACC has been larger in the mid-latitudes of the Northern Hemisphere (NH) than that at high- and low-latitudes. It is widely accepted that the ACC increase is the main reason for climate change, but the potential impacts of its spatial distribution on the climate system remain unclear. Therefore, we carried out two groups of 150-year experiments with the Community Earth System Model (CESM), using both spatially inhomogeneous (hereafter the SIC experiment) and homogenous (hereafter the SHC experiment) ACC increases in their settings. We found that the models’ divergences occurred over the NH mid-latitudes, the Arctic and the western part of the tropical Pacific. SHC overestimated (underestimated) climate warming over the Artic (mid-latitudes), which may be induced by the intensified westerly and weakened meridional heat exchange between mid- and high latitudes in the NH. Over the tropical Pacific, the overestimation of climate warming may be induced by intensified Walker circulation coupled with the La Niña climate mode. For the entire NH, relative to SIC, SHC overestimated the climate warming from 1850 to 1999 by ~10%. Meanwhile, the SHC experiment also overestimated the interannual variabilities in temperature and precipitation, resulting in more serious extreme events. These findings suggest that human contributions to climate warming and increased extreme events since the industrial revolution may be overestimated when using a spatially homogenous ACC.

Temperate trees could cope with climate change through phenotypic plasticity of phenological key events or adaptation in situ via selection on genetic variation. However, the relative contribution of local adaptation and phenotypic plasticity to phenological change is unclear for many ecologically important tree species. Here, we analyzed the leaf-out data of European beech (Fagus sylvatica L.) from 50 provenances planted in 7 trial sites. We first constructed a function between chilling accumulation (CA) and photoperiod-associated heat requirement (PHR) of leaf-out date for each provenance and quantified the relationship between parameters of the CA-PHR function and climatic variables at provenance origins by using the random forest model. Furthermore, we used the provenance-specific CA-PHR function to simulate future leaf-out dates under two climate change scenarios (RCP 4.5 and 8.5) and two assumptions (no adaptation and adaptation). The results showed that both CA, provenance, and their interactions affected the PHR of leaf-out. The provenances from southeastern Europe exhibited a stronger response of PHR to CA and thus flushed earlier than northwestern provenances. The parameters of the CA-PHR function were connected with climatic variables (e.g., mean diurnal temperature range, temperature seasonality) at the originating sites of each provenance. If only considering the phenotypic plasticity, the leaf-out date of European beech in 2070-2099 will advance by 6.8 and 9.0 days on average relative to 1951-2020 under RCP 4.5 and RCP 8.5, respectively. However, if F. sylvatica adapts to future climate change by adopting the current strategy, the advance of the leaf-out date will weaken by 1.4 and 3.4 days under RCP 4.5 and RCP 8.5, respectively. Our results suggest that the European beech could slow down its spring phenological advances and reduce its spring frost risk if it adopts the current strategy to adapt to future climate change.

The environment has been continuously changed, and it's a bitter truth that we can't minimize anthropogenic activities to mitigate harmful impacts on the environment. The changing environment is a great threat to food security by affecting crop yields. However, there is no comprehensive study to assess the environmental impact on the nutritional quality of the crops. In this study, we have investigated the nutritional profile and yield of maize crops around the globe and synchronized the findings with physiological reasoning. The study enlightens the time-scale activities of maize plant enzymes and describes their response to changing environments. The study also explained time-scale-based changes in the physiological conditions of maize crops against environmental dynamics around the globe. It also detected the impact of climate change on the deterioration of the nutritional quality of maize. The current study reports the activities of three different enzyme classes. It was noted that the photosynthesis-related enzyme activities were boosted after a sudden increase in carbon dioxide concentration. However, the drought years (2005-2010) decreased photosynthesis and increased oxidative enzyme activities. Overall, the glycemic index of the maize crop has been increased during the last four decades. However, the crop production threshold levels have been raised more quickly. The nutritional index values are alarming and have frequently been recorded under the threshold levels in recent years. The study paves a path for maize toward nutritional contents richness, ensuring food security and nutritional security in the future.

Changes in Earth’s albedo due to vegetation dynamics, snow cover, and land cover change have attracted much attention. However, the effects of vegetation dynamics on albedo have not been comprehensively documented according to its spatial (regional), temporal (within growing season), and spectral (visible, near-infrared, and shortwave) characteristics. This study examined the effects of vegetation greenness on albedo from 2000 to 2014 in China’s grasslands, which have considerable intra- and inter-annual variations, using remote sensing-based albedo and two-band Enhanced Vegetation Index (EVI2) data. Generally, we found an insignificant negative correlation between the shortwave (SW) albedo and EVI2 for grasslands in China. However, the visible (VIS) albedo was more sensitive to changes in vegetation greenness than near-infrared (NIR) albedo in China’s grasslands. The relationship between the NIR albedo and EVI2 was more complicated, especially in the Tibetan Plateau (TP), where the correlation was negative in the early growing season and positive in the late growing season; while the correlation between the NIR albedo and EVI2 was always negative in main part of Inner Mongolia (IM). The different albedo-EVI2 relationships in IM and TP may be related to differences in soil albedos. The higher sensitivity of the SW albedo to vegetation greenness change in IM, the stronger effect on land surface radiation budget. Our finding about vegetation-induced changes in albedo differ in space, time and spectral bands is expected to contribute to the improvement of land surface models.

This case study of the Hexi Corridor, Northwestern China, utilizes statistical methods to estimate quantitatively the interaction at a regional level between climate change, ancient social developments, and political coping strategies over the past 2000 years. The data is sourced from high-resolution reconstructions of climate series (temperature and precipitation), and historical records of cultivated land, war, population, and changes in regional administrative systems. The results show that moisture conditions played a more significant role than temperature in driving land reclamation in the Hexi Corridor. Analysis also showed a negative correlation between war frequency and the area of cultivated land in the Corridor over 20-year time intervals. Population growth was found to have a significant positive correlation with the cultivated land area during the study period. The results indicate that a climate-induced decline in agricultural production and the subsequent fluctuations in population could act as a trigger for social unrest, which is especially true at the mutual decadal time-scales. However, the interaction with administrative reform also suggests that, in the face of social and economic turmoil, a reasonable administrative hierarchy could strengthen the social governance of regional government, and promote social stability and economic development at a regional level. The study substantiates this notion with empirical quantitative evidence.

Spatio-temporal changes in the differentiation characteristics of eight consecutive phenological periods and their corresponding lengths were quantitatively analyzed based on long-term phenological observation data from 114 agro-meteorological stations in four maize growing zones in China. Results showed that average air temperature and growing degree- days (GDD) during maize growing seasons showed an increasing trend from 1981 to 2010, while precipitation and sunshine duration showed a decreasing trend. Maize phenology has significantly changed under climate change: spring maize phenology was mainly advanced, especially in northwest and southwest maize zones, while summer and spring-summer maize phenology was delayed. The delay trend observed for summer maize in the northwest maize zone was more pronounced than in the Huang-Huai spring-summer maize zone. Variations in maize phenology changed the corresponding growth stages length: the vegetative growth period (days from sowing date to tasseling date) was generally shortened in spring, summer, and spring-summer maize, although to different degrees, while the reproductive growth period (days from tasseling date to mature date) showed an extension trend. The entire growth period (days from sowing date to mature date) of spring maize was extended, but the entire growth periods of summer and spring-summer maize were shortened.

Background Adaptive crop management is critical to food security in a changing climate, but the respective contributions of climate change and crop management to yields remain unclear. Thus, we distinguished and quantified the respective contribution of climate change and crop management on wheat yield between 1981 and 2018 in China, using first-difference multivariate regression model. Results Wheat production in China has increased over the past four decades. Under the sole impact of climate change, wheat yield generally decreased (-5.45 to +1.09% decade-1 ). Crop management increased the wheat yield from 7.11 to 19.94% decade-1 . Sensitivities of wheat yield to climatic variables (average temperature, accumulated sunshine hours, accumulated precipitation) were spatially heterogeneous; notably, in spring-wheat planting areas, wheat yield was more susceptible to the negative impact of warming. In terms of relative contribution, the contribution of climate change to spring wheat yield was -24.08% to -5.41%, and the contribution to winter wheat was -4.98% to +34.69%. Crop management had a positive contribution to all wheat-growing areas (65.31-96.84%). Conclusion Crop management had a greater effect on wheat yield than climate change did. Among the three climatic variables investigated, average temperature had the dominant effect on wheat yield change; the impact of precipitation was minimal but mostly negative. The results provide insight regarding the contribution of climate change and crop management to wheat yield; adaptation measures may be more effective in planting areas where crop management contributes more, which will help stakeholders optimize crop management and adaptation strategies. © 2020 Society of Chemical Industry.

To inform targeted adaptation measures, comprehensive assessments of climate change impacts on agricultural systems are urgently needed. The current study analyzed the production (including phenology, yield, ET, and WUE) of major crops in the near future (2011–2040) through probabilistic assessment. The Crop-Environment Resource Synthesis (CERES)-Wheat/Maize model was driven by ensemble climate projections from five global climate models (GCMs) under three emission scenarios (RCP2.6, RCP4.5, RCP8.5). Results showed that: (1) Compared with the base period, the probability of advanced maturity for wheat and maize was 90.36–91.18% and 62.96–64.50%, respectively. The probability of yield reduction for wheat and maize was 64.12–68.93% and 40.44–41.41%, respectively. The probability of water use efficiency (WUE) reduction for wheat and maize was 51.09–53.94% and 35.86–37.93%, respectively. (2) In the absence of adaptation measures, substantial yield loss was found in major crop-producing areas, including the northern winter wheat planting area and Huang-Huai Plain spring-summer maize zone. The spatial overlap of the vulnerable area will exacerbate food insecurity. (3) The decrease in wheat yield and WUE were both greater than that of maize. Replacing highly sensitive crops with heat-tolerant varieties and dietary diversity should be advocated to cope with future climate change. The results will contribute to adaptive decision-making in China.

Spring warming substantially advances leaf unfolding and flowering time for perennials. Winter warming, however, decreases chilling accumulation (CA), which increases the heat requirement (HR) and acts to delay spring phenology. Whether or not this negative CA-HR relationship is correctly interpreted in ecosystem models remains unknown. Using leaf unfolding and flowering data for 30 perennials in Europe, here we show that more than half (7 of 12) of current chilling models are invalid since they show a positive CA-HR relationship. The possible reason is that they overlook the effect of freezing temperature on dormancy release. Overestimation of the advance in spring phenology by the end of this century by these invalid chilling models could be as large as 7.6 and 20.0 days under RCPs 4.5 and 8.5, respectively. Our results highlight the need for a better representation of chilling for the correct understanding of spring phenological responses to future climate change., Climate warming is advancing spring leaf unfolding, but it is also reducing the cold periods that many trees require to break winter dormancy. Here, the authors show that 7 of 12 current chilling models fail to account for the correct relationship between chilling accumulation and heat requirement, leading to substantial overestimates of the advance of spring phenology under climate change.

Precipitation extremes are among the most serious consequences of climate change around the world. The observed and projected frequency and intensity of extreme precipitation in some regions will greatly influence the social economy. The frequency of extreme precipitation and the population and economic exposure were quantified for a base period (1986–2005) and future periods (2016–2035 and 2046–2065) based on bias corrected projections of daily precipitation from five global climatic models forced with three representative concentration pathways (RCPs) and projections of population and gross domestic product (GDP) in the shared socioeconomic pathways (SSPs). The RCP8.5‐SSP3 scenario produces the highest global population exposure for 2046–2065, with nearly 30% of the global population (2.97 × 109 persons) exposed to precipitation extremes >10 days/a. The RCP2.6‐SSP1 scenario produces the highest global GDP exposure for 2046–2065, with a 5.56‐fold increase relative to the base period, of up to (2.29 ± 0.20) × 1015 purchasing power parity $‐days. Socioeconomic effects are the primary contributor to the exposure changes at the global and continental scales. Population and GDP effects account for 64–77% and 78–91% of the total exposure change, respectively. The inequality of exposure indicates that more attention should be given to Asia and Africa due to their rapid increases in population and GDP. However, due to their dense populations and high GDPs, European countries, that is, Luxembourg, Belgium, and the Netherlands, should also commit to effective adaptation measures., Key Points Global population and GDP exposures are highest for 2046–2065 in RCP8.5‐SSP3 and RCP2.6‐SSP1, 8.46 × 1010 person‐days and 2.29 × 1015PPP $‐daysIncreases in population and GDP are the dominant contributors, accounting for over 60% of future changes in socioeconomic exposureEffective adaptation is urgently needed for some European countries, for example, Luxembourg, the Netherlands, and Belgium, and in Asia and Africa

The effects of winter chilling, spring forcing temperature, and photoperiod on spring phenology are well known for many European and North American species, but the environmental cues that regulate the spring phenology of East Asian species have not yet been thoroughly investigated. Here, we conducted a growth chamber experiment to test the effects of chilling (controlled by different lengths of exposure to natural chilling conditions), forcing temperature (12, 15, or 18°C) and photoperiod (14 or 10 h) on first flowering date (FFD) of six woody species (three shrubs and three trees) native to East Asia. The three-way analysis of variance (ANOVA) separately for each species showed that the effects of chilling and forcing temperature were significant for almost all species (P < 0.05). Averaged over all chilling and photoperiod treatments, the number of days until FFD decreased by 2.3–36.1 days when the forcing temperature increased by 3°C. More chilling days reduced the time to FFD by 0.7–26 days, when averaged over forcing and photoperiod treatments. A longer photoperiod could advance the FFD by 1.0–5.6 days, on average, but its effect was only significant for two species (including one tree and one shrub). The effects of forcing temperature and photoperiod interacted with chilling for half of the studied species, being stronger in the low chilling than high chilling treatment. These results could be explained by the theory and model of growing degree-days (GDD). Increased exposure to chilling coupled to a longer photoperiod reduced the GDD requirement for FFD, especially when plants grew under low chilling conditions. However, shrubs (except Viburnum dilatatum) had lower chilling and heat requirements than trees, suggesting that, by leafing out sooner, they engage in a more opportunistic life strategy to maximize their growing season, especially before canopy closure from trees' foliage. Our results confirmed the varying effects of these three cues on the flowering phenology of woody species native to East Asia. In future climate change scenarios, spring warming is likely to advance the spring phenology of those woody species, although the reduced chilling and shorter photoperiod may partly offset this spring warming effect.

Current understanding of autumn phenological responses to climate change in deciduous tree species remains limited, mainly due to the difficulties in defining autumn events and the lack of knowledge about its mechanism. Here we applied a method based on measuring chlorophyll A (Chla) content in leaf tissue during the entire autumn senescence processes to appropriately quantify autumn phenological processes. Beginning of leaf coloring could be defined as when about 50% of the Chl was lost. End of leaf coloring could be defined as when about 95% of the Chl was lost. Then the mechanism behind the timing of autumn senescence responses to climate change through hormone regulation was studied for the first time. Four dominate deciduous tree species with representative senescence type (Salix babylonica, Ginkgo biloba, Acer mono, Cotinus coggygria) were chosen as the subject of study. Variations in climate factors (temperature, day length, precipitation, humidity) were recorded and nine major endogenous hormones (IAA, IPA, ZR, DHZR, GA3, GA4, ABA, MeJA, BR) in leaf tissues were monitored during the entire autumn senescence processes. The experimental results verified temperature and day length are the major climate factors affecting autumn phenology. Low temperature and short day length could result in the decrease of ZR level and the increase of ABA level in leaf tissue, which directly trigger/promote senescence. Meanwhile, low temperature and short day length could cause the decrease of MeJA level and the increase of GA3 and GA4 level, which regulate the timing of autumn senescence indirectly through ZR, ABA, and IAA. Our study improves the understanding of autumn phenological response to climate change in deciduous trees.

Heat escape-motivated travel, called “sunbird” tourism, has become increasingly important with global warming and associated urban heat island effects. This study proposes a new method based on defining “comfortable” calendar days, to identify regions thermally suitable for “sunbird” tourism (namely northern Northeast China, eastern Inner Mongolia Plateau, northern Xinjiang Province, eastern Qinghai-Tibet Plateau, and Yungui Plateau) and their comfortable periods in China. From 1961–1990 to 1987–2016, comfortable periods have extended by 5 to over 20 days in eastern Qinghai-Tibet Plateau and parts of Yungui Plateau, but shortened by 5 to over 20 days in northern Northeast China and eastern Inner Mongolia Plateau, corresponding to 9 and 21 locations respectively becoming suitable and no longer suitable for “sunbird” tourism. Moreover, comfortable periods are now much earlier in the eastern Inner Mongolia Plateau and have dramatically altered in terms of their temporal distribution over the eastern Qinghai-Tibet Plateau. Finally, we discuss the implications for tourism.

Phenological changes in crops affect efficient agricultural production and can be used as important biological indicators of local and regional climate change. Although crop phenological changes and their responses to climate change, especially temperature, have been investigated, the impact of agronomic practice such as cultivar shifts and planted date changes on crop phenology remains unclear. Here, we used a long-term dataset (1981–2010) of wheat phenology and associated local weather data from 48 agro-meteorological stations in four temperature zones in China to analyze phenological changes of spring and winter wheat. Trend analysis method was used to estimate changes in the date of growth stages and the duration of growth phases, while sensitivity analysis method was used to qualify the response of growth phase duration to mean temperature (Tmean), total precipitation (PRE), and total sunshine duration (SSD). Using the Crop Environment Resource Synthesis-wheat model, we isolated the impacts of climate change, cultivar selection, and sowing date on phenological change of wheat. Results show that phenological changes were greatest in the warm-temperate zone. Sensitivity analysis indicates that growth phase duration was generally negatively related to Tmean and positively related to PRE and SSD. The positive sensitivity response to Tmean occurred in the tillering to jointing and sowing to maturity growth periods in the warmer temperature zones, suggesting that warmer temperatures during the overwintering period hampered effective vernalization in winter wheat. Modeling results further indicate that reductions in wheat growth duration caused by climate change could be offset by the introduction of new cultivars with high thermal requirements and accelerated with delayed sowing date.

As one of the most populous countries, China has policies protecting the amount of land available for crop production, but it does not consider the quality of land. Thus, an important issue is the impact on crop production by land use change under such policies and by notable climate variability during the past decades. Using a productivity attenuation method, we estimated the climatic productivity of winter wheat (WWCP) in the North China Plain, based on land use classification data and daily weather data from 1980 to 2010. Impacts of historic climate variability and land use change on WWCP were quantified. Results indicate: (1) on average, WWCP for newly-increased dry land was lower than that for the lost land, which may result in reduced land quality associated with conversion. (2) In recent years, the increasing area of dry land provided sufficient wheat yield to compensate for the loss resulted from reduction of WWCP. (3) Both historic climate variability and land use change decreased WWCP, but the effects of the latter (within −1%) were less than those of the former (about −3%). Given the scarce land resource and rapidly growing food demand, the approach through expanding the area of cultivated land to maintain grain yield is not a long-term guarantee of food security. Thus, cultivated land conservation policy should shift from protecting land quantity into preserving land productivity. In addition, agriculture policies should further emphasize the critical role of adaptation strategies in coping with climate change. Obtaining higher yield production will depend upon adopting adaptation measures which could effectively mitigate effects of dramatic climate change or even take advantage of possible climate conditions.

Phenology is a reliable biological indicator for reflecting climate change. An examination of changes in crop phenology and the mechanisms driving them is critical for guiding regional agricultural activities in attempts to adapt to climate change. Due to a lack of records based on continuous long-term observation, studies on changes in multiple consecutive phenological stages throughout a whole growing season on a national scale are rarely found, especially with regard to the spatiotemporal differentiation of phenological changes. Using a long-term dataset (1981−2010) of wheat phenology collected from 48 agro-meteorological stations in China, we qualified the spatiotemporal changes of 10 phenological stages as well as the length of wheat growth phases. Results showed that climate and wheat phenology changed significantly during the growing seasons from 1981 to 2010. On average, on a national scale, dates of sowing (0.19 d a−1), emergence (0.06 d a−1), trefoil (0.05 d a−1), and milk ripe (0.06 d a−1) showed a delaying trend, whereas dates of tillering (−0.02 d a−1), jointing (−0.15 d a−1), booting (−0.21 d a−1), heading (−0.17 d a−1), anthesis (−0.19 d a−1), and maturity (−0.10 d a−1) showed an advancing trend. Furthermore, the vegetative growth phase and growing season were shortened by 0.23 and 0.29 d a−1, respectively, whereas the reproductive growth phase was lengthened by 0.06 d a−1. Trends in dates of phenological stages or length of growing phases varied across wheat-planting regions. Moreover, spatiotemporal differentiation of sensitivity in growing season length (GSL) to variations in climatic factors during the growing season between spring and winter wheat were remarkable. The GSL of spring (winter) wheat decreased (increased) with an increase in average temperature during the growing season. In all wheat-planting regions, the GSL increased with the increasing of total precipitation and sunshine duration during the growing season. In particular, the sensitivity of GSL to precipitation for spring wheat was weaker than for winter wheat, while the sensitivity of GSL to sunshine duration for spring wheat was stronger than for winter wheat. Recognition of the spatiotemporal differentiation of phenological changes and their response to various climatic factors will provide scientific support for decision-making in agricultural production.

Although gridded air temperature datasets share much of the same observations, different rates of warming can be detected due to different approaches employed for considering elevation signatures in the interpolation processes. Here, we examine the influence of varying spatiotemporal distribution of sites on surface warming in the long-term trend and over the recent warming hiatus period in China during 1951-2015. A suspicious cooling trend in raw interpolated air temperature time series is found in the 1950s, and 91% of which can be explained by the artificial elevation changes introduced by the interpolation process. We define the regression slope relating temperature difference and elevation difference as the bulk lapse rate of -5.6 oC/km, which tends to be higher (-8.7 oC/km) in dry regions but lower (-2.4 oC/km) in wet regions. Compared to independent experimental observations, we find that the estimated monthly bulk lapse rates work well to capture the elevation bias. Significant improvement can be achieved in adjusting the interpolated original temperature time series using the bulk lapse rate. The results highlight that the developed bulk lapse rate is useful to account for the elevation signature in the interpolation of site-based surface air temperature to gridded datasets and is necessary for avoiding elevation bias in climate change studies.

Crop phenology is co-determined by climate change and crop management. Over recent decades, climate change-related alterations in crop phenology have been observed and reported for various global crops. However, attributing changes in crop phenology to climate change is difficult, because there have been concurrent changes in crop management. In this paper, we isolated and quantified the impacts of climate change and crop management on the changes of wheat phenology in China, during the period 1981–2010, using a first-difference multiple regression model. Our results shows: (1) based on observed phenological data, in spring/winter wheat, the mean sowing and emergence date were delayed by 0.91/2.29 and 0.39/0.73 days decade−1; mean anthesis and maturity date advanced by 1.05/2.28 and 0.01/1.42 days decade−1; mean length of vegetative growth period (VGP) and whole growth period (WGP) were shortened by 1.09/2.86 and 0.89/3.69 days decade−1; mean length of reproductive growth period (RGP) was prolonged by 0.55/0.61 days decade−1. (2) At most stations, changing direction of wheat phenology affected by isolated impacts of climate change or crop management was consistent with that affected by combined impacts of climate change and crop management. (3) For observed trends of most phenological stages and growth periods, relative contribution from climate change was smaller than from crop management, and average temperature contributed the most among the three contributors (average temperature, cumulative precipitation, and cumulative sunshine hours) to isolated impacts of climate change on wheat phenology. (4) Crop management over the three decades was shown to have helped reduce the lengths of VGP and WGP, but increase the length of RGP for both spring and winter wheat, implying that shorter-duration varieties with a higher yield or better yield stability in changing climate might have been introduced by farmers.

Climate change effects on global food security are not only limited to its effects on the yield of cereals but also their nutritional quality. However, climate change effects on crop nutritional quality, particularly grain protein concentration (PC) on a large geographical scale have not yet been quantified in China. For this purpose, we assessed the effects of three key climatic factors (temperature, precipitation, and solar radiation) on wheat PC in ten wheat-growing areas of China using a series of statistical models on a county-level PC dataset. The results demonstrated that the average PC in China from 2006 to 2018 ranged from 12.01% to 14.50% across the ten areas, with an obvious spatial difference pattern showing an increase in PC from south to north and from west to east. The sensitivity analysis indicated that PC showed a positive response to variation in the increasing temperature, and the PC of wheat grown in the Huanghuai area was less affected than the PC of wheat grown in other areas. Conversely, solar radiation posed negative effects on the PC in the southwestern area, whereas precipitation had intricate effects on the PC in all areas. Besides, the highest explanation of climate variability during five growth periods contributed 26.0%–47.6% of the PC variability in the northeastern area, whereas the lowest explanation of climate variability during five growth periods only accounted for 2.5%–3.7% of PC variability in the Yangtze River area. Our study further demonstrated that the effects of climate change on wheat grain PC in China were spatially heterogeneous with higher effects on PC in spring wheat-growing areas as compared to winter wheat-growing areas. We suggested that the northern and the northeastern area in China could be developed as alternative areas to produce wheat with high grain PC in the face of climate warming.

The emergence of complex society is a milestone in the history of human society evolution. China is one of the few regions in the world where the earliest complex society appeared; however, its driving mechanisms remain unresolved. On the base of available evidence from both archaeology and Holocene climate, in combination with agency theory, this study attempts to address the driving mechanisms for the simultaneous emergence of complex societies in multiple areas of China around 5.5 cal ka BP. It is hypothesized that three factors, including climate change, population growth, and circumscription, jointly act and cause regional population-resource imbalance and trigger inter-group conflicts and wars. Such competitions provide the opportunity for some power-pursuing agents to break the restriction of social leveling mechanism and to become the centralized decision-making leaders, which further lead to the emergence of incipient large-scale complex societies. Increase in extreme climate events during 6.0–5.0 cal ka BP cooling period causes frequent occurrence of resource stress and increase in the frequency of inter-group competitions, which creates conditions for the legitimation, institutionalization, and persistence of centralized leadership, and finally leads to the formation of persistent institutionalized inequity. Our research result can explain not only the process and mechanism of complex society formation, but also two phenomena which cannot be reasonably explained by previous theories, that are, why the earliest complex societies in China emerge around 5.5 cal ka BP, and why they appear simultaneously in multiple regions.

Phenology has been regarded as an essential bio-indicator of climate change widely. Quantifying the crop phenological changes caused by climate change and anthropogenic-management practices can help formulate effective climate change adaptation strategies. In this study, the effects of climate change and anthropogenic-management practices on maize phenology (spring, summer, and intercropping maize) in China were distinguished based on historical meteorological and phenological data (1981–2010) of 114 stations using the first-order difference regression method. Our results show: (1) The vegetative growing period of spring and intercropping maize was extended, whereas that of summer maize was shortened. The reproductive growing periods of spring, summer, and intercropping maize were extended. (2) Isolated impacts of climate change shortened the vegetative growing period of spring maize, summer maize, and intercropping maize by 0.19, 1.06, and 3.12 d decade−1, respectively, while the reproductive growing period was extended by 0.19, 0.74, and 3.47 d decade−1, respectively. (3) The contribution of temperature to maize phenology was greater in the northwest inland maize zone and north spring maize zone than in other regions, whereas the contribution of sunshine hours was higher in Huang-Huai Plain intercropping maize zone and the southwest mountain hills maize zone. (4) The effects of anthropogenic-management practices on maize phenological stages such as sowing, emergence, and maturity were generally greater than that of climate change, which has delayed the phenological stages of summer and intercropping maize and extended the growing period of spring maize. The focus should be paid to the emergence, jointing, and milky stages to increase the water use efficiency in the northwest inland maize zone. The findings provide a scientific basis for improving the adaptability of agricultural systems in climate change.

With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data (1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a-1. But the stages from emergence to maturity occurred earlier (0.1 d·10a-1

This paper presents new high-resolution proxies and paleoclimatic reconstructions for studying climate changes in China for the past 2000 years. Multi-proxy synthesized reconstructions show that temperature variation in China has exhibited significant 50–70-yr, 100–120-yr, and 200–250-yr cycles. Results also show that the amplitudes of decadal and centennial temperature variation were 1.3°C and 0.7°C, respectively, with the latter significantly correlated with long-term changes in solar radiation, especially cold periods, which correspond approximately to sunspot minima. The most rapid warming in China occurred over AD 1870–2000, at a rate of 0.56° ± 0.42°C (100 yr)−1; however, temperatures recorded in the 20th century may not be unprecedented for the last 2000 years, as data show records for the periods AD 981–1100 and AD 1201–70 are comparable to the present. The ensemble means of dryness/wetness spatial patterns in eastern China across all centennial warm periods illustrate a tripole pattern: dry south of 25°N, wet from 25°–30°N, and dry to the north of 30°N. However, for all centennial cold periods, this spatial pattern also exhibits a meridional distribution. The increase in precipitation over the monsoonal regions of China associated with the 20th century warming can primarily be attributed to a mega El Ni˜no–Southern Oscillation and the Atlantic Multidecadal Oscillation. In addition, a significant association between increasing numbers of locusts and dry/cold conditions is found in eastern China. Plague intensity also generally increases in concert with wetness in northern China, while more precipitation is likely to have a negative effect in southern China.

Response and feedback of land surface process to climate change is one of the research priorities in the field of geoscience. The current study paid more attention to the impacts of global change on land surface process, but the feedback of land surface process to climate change has been poorly understood. It is becoming more and more meaningful under the framework of Earth system science to understand systematically the relationships between agricultural phenology dynamic and biophysical process, as well as the feedback on climate. In this paper, we summarized the research progress in this field, including the fact of agricultural phenology change, parameterization of phenology dynamic in land surface progress model, the influence of agricultural phenology dynamic on biophysical process, as well as its feedback on climate. The results showed that the agriculture phenophase, represented by the key phenological phases such as sowing, flowering and maturity, had shifted significantly due to the impacts of climate change and agronomic management. The digital expressions of land surface dynamic process, as well as the biophysical process and atmospheric process, were improved by coupling phenology dynamic in land surface model. The agricultural phenology dynamic had influenced net radiation, latent heat, sensible heat, albedo, temperature, precipitation, circulation, playing an important role in the surface energy partitioning and climate feedback. Considering the importance of agricultural phenology dynamic in land surface biophysical process and climate feedback, the following research priorities should be stressed: (1) the interactions between climate change and land surface phenology dynamic; (2) the relations between agricultural phenology dynamic and land surface reflectivity at different spectrums; (3) the contributions of crop physiology characteristic changes to land surface biophysical process; (4) the regional differences of climate feedbacks from phenology dynamic in different climate zones. This review is helpful to accelerate understanding of the role of agricultural phenology dynamic in land surface process and climate feedback.

Based on historical records of extreme climate events and population densities in Gansu and Shaanxi, and information on climate change, populations, new cultivated cropland, and administrative system reform in Xinjiang, this study explores the interaction between climate change, migration, and regional administrative reform in the middle Qing Dynasty. The results showed that the surge in population migration from Gansu and Shaanxi to Xinjiang during 1760–1820 was caused by extreme climate events (droughts and floods) and population pressure in Gansu and Shaanxi. During 1760–1880, the climate in Xinjiang was unusually cold and humid, which was highly conducive to abundant regional water resources. This provided favorable conditions for farmland irrigation and further promoted agricultural cultivation, population growth, and town development within this region. Additionally, the interactions between climate change and the above-mentioned social factors, which acted as driving forces, spurred the reform in the administrative system of Xinjiang whereby the military administration system was transformed to a province administration system. Through this reform, the Qing government managed to restore peace and stability in Xinjiang. This study contributes to a better understanding of climate-related population migration and enhances our knowledge of the impact-response chain between climate change, ancient social developments, and political coping strategies, especially in regional administrative reform.

Phenology is an important indicator of annual plant growth and is also widely incorporated in ecosystem models to simulate interannual variability of ecosystem productivity under climate change. A comprehensive understanding of the potentials of current algorithms to detect the start and end for growing season (SOS and EOS) from remote sensing is still lacking. This is particularly true when considering the diverse interactions between phenology and climate change among plant functional types as well as potential influences from different sensors. Using data from 60 flux tower sites (376 site-years in total) from the global FLUXNET database, we applied four algorithms to extract plant phenology from time series of normalized difference vegetation index (NDVI) from both MODIS and SPOT-VGT sensors. Results showed that NDVI-simulated phenology had overall low correlation (R 2

The community of climate change impact assessments and adaptations research needs regional high-resolution (spatial) meteorological data. This study produced two downscaled precipitation datasets with spatial resolutions of as high as 3 km by 3 km for the Heihe River Basin (HRB) from 2011 to 2014 using the Weather Research and Forecast (WRF) model nested with Final Analysis (FNL) from the National Center for Environmental Prediction (NCEP) and ERA-Interim from the European Centre for Medium-Range Weather Forecasts (ECMWF) (hereafter referred to as FNLexp and ERAexp, respectively). Both of the downscaling simulations generally reproduced the observed spatial patterns of precipitation. However, users should keep in mind that the two downscaled datasets are not exactly the same in terms of observations. In comparison to the remote sensing-based estimation, the FNLexp produced a bias of heavy precipitation centers. In comparison to the ground gauge-based measurements, for the warm season (May to September), the ERAexp produced more precipitation (root-mean-square error (RMSE) = 295.4 mm, across the 43 sites) and more heavy rainfall days, while the FNLexp produced less precipitation (RMSE = 115.6 mm) and less heavy rainfall days. Both the ERAexp and FNLexp produced considerably more precipitation for the cold season (October to April) with RMSE values of 119.5 and 32.2 mm, respectively, and more heavy precipitation days. Along with simulating a higher number of heavy precipitation days, both the FNLexp and ERAexp also simulated stronger extreme precipitation. Sensitivity experiments show that the bias of these simulations is much more sensitive to micro-physical parameterizations than to the spatial resolution of topography data. For the HRB, application of the WSM3 scheme may improve the performance of the WRF model.

Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change (ABM/LUCC), an ecosystem process model (PnET-II), and a forest dynamic landscape model (LANDIS-II) to simulate the change of forest aboveground biomass (AGB) which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that: (1) land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County. (2) Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7% (RCP2.6 + land use), 57.2% (RCP4.5 + land use), and 56.9% (RCP8.5 + land use) by 2050, which is in comparison to the results under separate RCPs without land use disturbance. (3) The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function, and developing measures for sustainable forest management.

A climate event at 7.5–7.0 cal ka BP (thousand calibrated years before present) has been recognized. This event is important for foreseeing the possible response of the climate system to global warming and for interpreting considerable societal change, but it has heretofore lacked a systematic review. Here, we summarize previously published paleoclimate records spanning this event from 47 sites around the world. The proxy evidence from a variety of paleo-archives, including lake sediments, speleothems, marine sediments, and ice cores, provides a clear picture of this climate change. The synthesis results show a weaker Asian summer monsoon, in contrast to a stronger South American summer monsoon during the event. The event also involves dramatic cooling and wetter conditions in north-central Europe and in western North America, widespread aridity across Africa, contrasting patterns of precipitation variability throughout the Mediterranean, and notable cooling over the polar region, suggesting that it is a worldwide climate event. Comparison of paleoclimate records with climate-forcing time series gives likely climate controls for the event. The close correspondence in time of solar irradiance minima, strong volcanic eruptions, the meltwater flux into the North Atlantic, an orbitally induced decrease in solar insolation, and climate changes indicated by proxy data suggest possible linkages. More quantitative reconstructions and higher resolution climate records are needed to fully capture the magnitude, timing, duration, and nature of this event, which will be of considerable relevance to modeling.

Continuous long-term temperature sensitivity (ST) of leaf unfolding date (LUD) and main impacting factors in spring in the period 1978–2014 for 40 plant species in Mudanjiang, Heilongjiang Province, Northeast China, were analyzed by using observation data from the China Phenological Observation Network (CPON), together with the corresponding meteorological data from the China Meteorological Data Service Center. Temperature sensitivities, slopes of the regression between LUD and mean temperature during the optimum preseason (OP), were analyzed using 15-year moving window to determine their temporal trends. Major factors impacting ST were then chosen and evaluated by applying a random sampling method. The results showed that LUD was sensitive to mean temperature in a defined period before phenophase onset for all plant species analyzed. Over the period 1978–2014, the mean ST of LUD for all plant species was − 3.2 ± 0.49 days °C−1. The moving window analysis revealed that 75% of species displayed increasing ST of LUD, with 55% showing significant increases (P

International audience; Growing evidence indicates that the risk of heat extremes will increase as climate change progresses and create a significant threat to public health and the economy. Socioeconomic exposure is the key component for assessing the risk of such events. To quantify socioeconomic exposure to heat extremes for 2016–2035 and 2046–2065, we use the projections of five global climate models forced by using three representative concentration pathways (RCPs) and projections of population and gross domestic product (GDP), and we take into account the geographic change in the distribution in shared socioeconomic pathways (SSPs). The exposure of the global population for 2046–2065 is the greatest under the RCP8.5-SSP3 scenario, up to 1037(±164) × 109 person-days, and the global GDP exposure for 2046–2065 is greatest under the RCP2.6-SSP1 scenario, up to 18(±2) × 1015 dollar-days. Asia has the highest exposure among all continents for both population and GDP, accounting for over half of the global exposure. Africa has the largest increase in exposure, with the annual population and GDP exposures increasing by over 9- and 29-fold, respectively, compared with the base period (1986–2005). The effect of climate makes the dominant contribution (47%–53%) globally for the change in population exposure. Changes in the geographic distribution of GDP cause nearly 50% of the total change in GDP exposure for 2016–2035. Mitigating emissions of greenhouse gases, either at the level of the RCP2.6 scenario or at a more ambitious target, is essential for reducing socioeconomic exposure to heat extremes. In addition, designing and implementing effective measures of adaptation are urgently needed in Asia and Africa to aid socioeconomic systems suffering from heat extremes due to climate change.

The impact of spring temperature forcing on the timing of leaf unfolding of plants (temperature sensitivity, ST) is one important indicator of how and to what degree plant species track climate change. Fu et al. (Nature 526:104–107, 2015) found that ST has significantly decreased from the 1980–1994 to the 1999–2013 period for seven mid-latitude tree species in Europe. However, long-term changes in ST over the past 60 years are still not clear. Here, using in situ observations of leaf unfolding for seven dominant European tree species, we analyze the temporal change in ST over decadal time scales extending the data series back to 1951. Our results demonstrate that ST shows no statistically significant change within shifting 30-year windows from 1951 to 2013 and remains stable between 1951–1980 and 1984–2013 (3.6 versus 3.7 days °C−1). This result suggests that the significant decrease in ST over the past 33 years could not be sustained when examining the trends of phenological responses in the long run. Therefore, we could not conclude that tree spring phenology advances will slow down in the future, and the ST changes in warming scenarios are still uncertain.