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Henan Province is the birthplace of Chinese civilization and one of the earliest human settlements, which means that the area has an important national cultural heritage. Traditional villages are an important facet of this cultural heritage, and studying their spatiotemporal characteristics in different periods has important theoretical and practical significance for the sustainable development and protection of cultural heritage in the region. This paper takes the traditional villages of the Yellow River basin in Henan Province that were formed before 1919 as the research object. Information on the ancient river was obtained through a literature search as well as via field research, and the important tributaries of the Yellow River in different periods were mapped using ArcGIS 10.0 software. The nearest neighbor index, kernel density estimation, standard deviation ellipse and other methods were adopted to analyze the spatiotemporal characteristics of the traditional villages. The factors that influenced the evolution of traditional villages were explored in depth by combining changes in the course of the river and water conservancy projects. The results show that the formation of traditional villages along the Yellow River in Henan Province has experienced a historical track of growth, contraction, growth and prosperity and stability. The traditional villages along the Yellow River in Henan Province generally show a clustered pattern, forming a dense concentration of traditional villages in the middle reaches of the Yellow River. The center of gravity shows a migration trend from southeast to northwest. In terms of influencing factors, the spatiotemporal evolution of the relationship between villages and their distance to water is closely related to climatic fluctuations, changes in channel, water conservancy projects and social and cultural factors. This paper deepens our understanding of the relationship between traditional village evolution and watersheds by improving the consistency between village spatial distribution and historical geography and provides a useful theoretical reference for the sustainable development of China's traditional villages. [ABSTRACT FROM AUTHOR]

The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

This paper used original survey data in Shandong province of China to depict local farmers' perceptions of combined climatic and market risks, and their adaptive behaviors. Two Logit models were developed to capture the empirical relationship between farmers' risk perception of the combined risks and adaptive behaviors. Results show that farmer's risk perception of climate change and market significantly affected their adoption behavior of adaptive measures, including perception of rainfall decrease, gale decrease, drought increase, and price fall of agricultural products. Moreover farmers' adaptive behaviors are more sensitive to their perceptions of extreme climatic events. Addition of demographic factors can improve the explanatory capacity of the Logit model. As illustrated by the models, male and better educated farmers have greater willingness to take actions for averting risks, while household heads with bigger farm are more reluctant. A majority of respondents chose to construct farm structure for irrigation and water conservation to avert climatic risks. Insurance, which is regarded as an effective tool to help farmers mitigate risks and avoid losses, has not been sufficiently accepted by farmers in rural areas in Shandong province. This underscores the need of effective communication of knowledge to enhance farmers' coping capacity and to encourage their active response to risk. [ABSTRACT FROM AUTHOR]

Although ski tourism in China is experiencing a boom, and the number of operating ski areas has significantly increased, the influence of climate change on the future development of China's ski industry has so far largely been overlooked. This paper addresses this important gap by applying the ski season simulation model SkiSim 2.0 at 116 ski areas. Four main indicators of climate change impact were examined: ski season length, operational ski days in economically important season segments, technically produced snow and snowmaking requirements. For all ski resorts in China and all climate change scenarios, average ski seasons are projected to shorten (− 4 to − 61% RCP 4.5; − 6 to − 79% RCP 8.5 in the 2050s) while snowmaking needs increase (27 to 51% RCP 4.5; 46 to 80% RCP 8.5 in the 2050s). The results indicate that high regional differences in climate change vulnerability exist. The implications for altered competitiveness and development potential of the ski industry in China are discussed. [ABSTRACT FROM AUTHOR]

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As the largest terrestrial organic carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle, but it is easily affected by land use and climate change. The Huang-Huai-Hai Plain (HHHP) in China, which is dominated by dry farming, is experiencing rapid farmland loss and gain (farmland use transition), which may cause drastic changes in SOC storage. To clarify the effects of farmland use transition on SOC in dry farming areas, this study adopted a land use transition matrix and spatial analyst tool to explore the characteristics of farmland use transition and its effects on SOC content and stocks in the 200 cm soil layer in the HHHP from 2000 to 2020. The results showed that the farmland use transition in this area during that time period resulted in a net decrease of 16.06 × 103 km2 of farmland, of which urban built-up land and rural settlements led to a net reduction of farmland by 9.74 × 103 km2 and 6.43 × 103 km2, respectively, which was mainly affected by climate, topography, and economic factors. In addition, the farmland use transition resulted in a net increase in SOC storage of 6.13 Tg C, contributing 44.32% of the net increase. This is likely because the change in land use type led to a change in soil bulk density and soil gravel content while altering the SOC content, which in turn affected the SOC stock. This study has important implications for addressing global climate change and maintaining sustainable agricultural resources. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1◦ scale over China from 1990 to 2100 and investigated the temporal evolution of Köppen-Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions (7%-8% of China's land area) by 2010, including rapid replacement of mixed forest (Dwb) by deciduous forest (Dwa) over Northeast China, strong shrinkage of alpine climate type (ET) on the Tibetan Plateau, weak northward expansion of subtropical winterdry climate (Cwa) over Southeast China, and contraction of oceanic climate (Cwb) in Southwest China. Under all future RCP (Representative Concentration Pathway) scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010-30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario (RCP8.5), sub-polar continental winter dry climate over Northeast China would disappear by 2040-50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9% and 50.8% of China's land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China's ecoregions in future decades. [ABSTRACT FROM AUTHOR]

This paper aims to analyse what shapes farmers' vulnerability and adaptation strategies in the context of rapid change. Xinjiang is semi-arid, with extremes of temperature, growing seasons and winds. Favourable socioeconomic conditions have boosted the wellbeing of farmers in the past decades. Interviews with forty-seven farmers led to the categorization of five groups according to the predominant type of farming activity: animal farmers, government farmers (leasing land from the Xinjiang Production and Construction Group), crop farmers, agri-tourism operators and entrepreneurs. High government support has aided farmers to deal with climate challenges, through advanced technology, subsidies and loans. Farmers, however, greatly contribute to their own high adaptive capacity through inventiveness, flexibility and a high knowledge base. Although the future climate will entail hotter temperatures, farmers can be seen as generally well equipped to deal with these challenges because of the high adaptive capacity they currently have and utilize. Those that are most vulnerable are those that have difficulty to access credit e.g. animal farmers and those that do not want to change their agricultural systems e.g. from pastoral lifestyles to include tourism-based operations. [ABSTRACT FROM AUTHOR]

This paper provides a review of paleoclimate modeling activities in China. Rather than attempt to cover all topics, we have chosen a few climatic intervals and events judged to be particularly informative to the international community. In historical climate simulations, changes in solar radiation and volcanic activity explain most parts of reconstructions over the last millennium prior to the industrial era, while atmospheric greenhouse gas concentrations play the most important role in the 20th century warming over China. There is a considerable model-data mismatch in the annual and boreal winter temperature change over China during the mid-Holocene [6000 years before present (ka BP)], while coupled models with an interactive ocean generally perform better than atmospheric models. For the Last Glacial Maximum (21 ka BP), climate models successfully reproduce the surface cooling trend over China but fail to reproduce its magnitude, with a better performance for coupled models. At that time, reconstructed vegetation and western Pacific sea surface temperatures could have significantly affected the East Asian climate, and environmental conditions on the Qinghai-Tibetan Plateau were most likely very different to the present day. During the late Marine Isotope Stage 3 (30-40 ka BP), orbital forcing and Northern Hemisphere glaciation, as well as vegetation change in China, were likely responsible for East Asian climate change. On the tectonic scale, the Qinghai-Tibetan Plateau uplift, the Tethys Sea retreat, and the South China Sea expansion played important roles in the formation of the East Asian monsoon-dominant environment pattern during the late Cenozoic. [ABSTRACT FROM AUTHOR]

China is facing the challenge of climate change and environmental protection in line with the promotion of sustainable development goals. Climate, environmental, and economic policy can each individually impact the effectiveness of other policies in the process of implementation. Understanding synergies among policy measures and identifying the co-benefits of environmental sustainable development generated by them is the focus of the paper. Because of existing restrictions in current research methods, the research community lacks the capacity to detect the interrelation among environmental, economic, and social development. Co-benefit research has gradually become an important area on sustainable development. Based on endogenous economic growth theory, we build a modified endogenous growth model to determine the optimal rates of economic growth, environmental pollution, energy input, and other factors in the context of co-benefits. Further empirical analysis is given which is missing in previous studies in this field. The empirical analysis reveals that China's actual GDP, consumption, energy input, and physical capital growth rates are much higher than the optimal growth rate. However, the human capital and environmental pollution control growth rates are slower than the optimal values. Although China has a rapid growth in economy, the optimal level of comprehensive co-benefits has not been reached yet. [ABSTRACT FROM AUTHOR]

In the context of climate change, the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China, posing a serious threat to the socioeconomic development in the region. This study took tropical cyclones–extreme precipitation–flash floods as an example to carry out a risk assessment of flash floods under climate change in the Yantanxi River Basin, southeastern China. To obtain the flash flood inundation characteristics through hydrologic–hydrodynamic modeling, the study combined representative concentration pathway (RCP) and shared socioeconomic pathway (SSP) scenarios to examine the change of flash flood risk and used the geographical detector to explore the driving factors behind the change. The results show that flash flood risk in the Yantanxi River Basin will significantly increase, and that socioeconomic factors and precipitation are the main driving forces. Under the RCP4.5-SSP2 and RCP8.5-SSP5 scenarios, the risk of flash floods is expected to increase by 88.79% and 95.57%, respectively. The main drivers in the case study area are GDP density (q = 0.85), process rainfall (q = 0.74), asset density (q = 0.68), and population density (q = 0.67). The study highlights the influence of socioeconomic factors on the change of flash flood disaster risk in small river basins. Our findings also provide a reference for regional planning and construction of flood control facilities in flash flood-prone areas, which may help to reduce the risk of flash floods. [ABSTRACT FROM AUTHOR]

This study examined the effects of climate change on rice production in 30 Chinese provinces spanning 1998–2017. The study used the pooled mean group technique to capture the long-run and short-run effects of changing climatic conditions on rice production. It further employed the Dumitrescu–Hurlin panel causality test to examine the path of causality between the key variables and rice production. The study found that, in the long run, average temperature negatively influenced rice production, but average rainfall had a positive effect on rice production. The results indicated that the cultivated area and fertilizer usage were positively related to rice production in the long run. The short-run results accentuated that average temperature favourably influenced nationwide rice production, whereas average rainfall had no substantial effect on national rice production. The cultivated area had a significant positive short-term relationship with rice production, although the impact of fertilizer usage on rice production was negligible in the short run. Besides, the results established a bidirectional causality between rice output and the cultivated area, but there was a one-way causality running from fertilizer usage to rice output. Finally, the results indicated that, except for rainfall, a unidirectional causality exists between temperature and rice production. The study, therefore, recommends that in the case of crop failure due to weather conditions, policymakers could implement a new pricing policy to mitigate the deterioration of the farmers' income. The government must also develop and implement an insurance scheme that compensates farmers for catastrophes induced by rainfall deficiency. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forest dieback due to climate change poses a risk to mountain forests throughout the world, and has severe consequences in terms of lost ecosystem services for forest stakeholders. This contribution aims to analyze how forest stakeholders perceive forest dieback, and the way in which they adapt to it. We conducted qualitative in-depth interviews in three mid-mountain case study areas in France, Germany, and China, enabling a cross-comparison of different settings affected by forest dieback. Results show that forest dieback is not a new phenomenon for stakeholders who consider that it has increased over the last few decades, due to rising temperatures and extreme weather events. In all survey areas, respondents consider forest dieback as tangible proof of climate change, identifying context-specific impacts with varying levels of severity. Cause-effect relationships are not easy to establish. Forest stakeholders are unable to determine whether climate change is a triggering or aggravating factor. For adaptive strategies, respondents can be grouped into three main profiles: proactive, reactive, and wait-and-see forest owners. These types of stakeholders differ in terms of their investment capacities, economic dependency, emotional attachment to forests, knowledge level, and capacity to obtain actionable information through participation in institutional networks. [ABSTRACT FROM AUTHOR]

In this Perspective, we discuss whether in times of quickly proceeding global environmental change, radical global interventions like "climate engineering" may gain legitimacy in China and eventually be deployed or supported. We argue that one cornerstone for whether climate engineering, and solar radiation management in particular, could gain legitimacy in China, is its current weather modification programme. In China, weather modification is institutionalized and deployed on a large scale, and current narratives around the legitimacy to intervene into the local climate may provide a rationale for interventions such as solar radiation management. In the end, in the same way as Deng Xiaoping coined the phrase "stepping on stones to cross the river" in the era of China's Industrial Civilization, narrating China's "Ecological Civilization" may want to make use of "seeding the clouds to reach the sky". [See ESM for a summary of the article in Chinese.] [ABSTRACT FROM AUTHOR]

Background: The accuracy in estimating forest ecosystem carbon storage has drawn extensive attention of researchers in the field of global climate change. However, incomparable data sources and various estimation methods have led to significant differences in the estimation of forest carbon storage at large scales. Methods: In this study, we reviewed fundamental types of forest carbon storage estimation methods and their applications in China. Results: Results showed that the major forest carbon storage estimation methods were classified into 3 major categories and 15 subcategories focusing on vegetation carbon storage estimation, soil carbon storage estimation, and litter carbon storage estimation, respectively. The application in China showed that there have been 3 development stages of research in China since the 1990s. Studies of forest carbon storage estimation in province scales were conducted more frequently in the northeastern, eastern and southwestern provinces such as Zhejiang, Heilongjiang and Sichuan with high forest coverage or large forest area. Inventory-based methods, soil type method, and biomass model were the main forest estimation methods used in China, focusing on vegetation, soil and litter carbon storage estimation respectively. Total forest carbon storage of China was approximate 28.90 Pg C, and the average vegetation carbon density (42.04 ± 5.39 Mg·ha− 1) was much lower than that of the whole world (71.60 Mg·ha− 1). Vegetation carbon density from average biomass method was the highest (57.07 Mg·ha− 1) through comparing nine types of vegetation carbon storage estimation methods applied during 1989 to 1993. Conclusions: Many studies on forest carbon storages have been carried out in China at patch scales or regional scales. These efforts enabled the research of forest carbon storage to reach a relatively advanced stage. Meanwhile, the accumulation of massive research data provides the basis for subsequent research work. Some challenges are also existing. This review could provide a reference for more accurate estimation of forest carbon storage in the future. [ABSTRACT FROM AUTHOR]

Vegetation growth and phenology are largely regulated by base temperature (Tb) and thermal accumulation. Hence, the growing degree-days (GDD) and growing season (GS) calculated based on Tb have primary effects on terrestrial ecosystems, and could be changed by the significant warming during the last century. By choosing 0, 5, and 10 °C, three key Tb for vegetation growth, the GDD and GS in China during 1960–2011 were developed based on 536 meteorological stations with homogenized daily mean temperatures. Results show that both the GDD and GS showed positive sensitivity to the annual mean temperature. The start of the growing season (SOS) has advanced by 4.86–6.71 days, and the end of the growing season (EOS) has been delayed by 4.32–6.19 days, lengthening the GS by 10.76–11.02 days in China as a whole during 1960–2011, depending on the Tb chosen. Consistently, the GDD has totally increased 218.92–339.40 °C days during the 52 years, with trends more pronounced in those based on a lower Tb. The GDD increase was significant (Mann–Kendall test, p < 0.01) over China except for the north of Southwest China, while the significant GS extension only scattered over China. Whereas the extensions of GS0 and GS5 were dominated by the advance in SOS, the GS10 extension was closely linked to the delay in EOS. Regionally, the GS extension in the eastern monsoon zone and northwest arid/semi-arid zone was driven by the advance in SOS and delay in EOS, respectively. Moreover, each variation has a substantial acceleration mostly in 1987 or 1996, and a speed reduction or even a trend reversal in the early 2000s. Changes in the thermal growing degree-days and season are expected to have great implications for biological phenology, agricultural production, and terrestrial carbon cycle in the future. [ABSTRACT FROM AUTHOR]

This study investigated climatic determinants for regional greenness in China and spatially variable correlations between climatic determinants and vegetation in specific regions using the geographical detector and geographically weighted regression (GWR) methodologies. The analyses were based on normalized difference vegetation index (NDVI) and interpolations of climatic determinants from 652 Chinese meteorological stations. The study period (1982–2013) was divided into two stages (T1–T2) before and after the inflection year identified by the accumulative anomaly of NDVI. Three typical regions (R1–R3) were then selected according to the same NDVI variation trend as China in the two periods. Precipitation was the dominant climatic factor of NDVI in China, and the effect of temperature on greenness increased with warming from T1 to T2. In a relatively arid region (R1), the effect of precipitation in T2 was further strengthened compared to T1. Meanwhile, the effect of minimum temperature in T2 also increased compared with T1 in a relatively humid region (R2), becoming the major climatic determinant. In addition to the regional differentiation, spatial variability was investigated by comparing normalized coefficients of GWR for climatic determinants; this showed significant spatial heterogeneity within each region. Temperature impact areas also existed within precipitation-dominated regions (R1 and R3), where areas of precipitation impact expanded from T1 to T2. Furthermore, regression coefficients between NDVI dynamics and climate variability revealed relationships between regional differentiation and spatial variability. For example, the increasing precipitation rate could mediate the adverse impacts on greenness caused by the higher warming rate in relatively arid regions (R1). [ABSTRACT FROM AUTHOR]

The frequency, intensity, and duration of extreme temperature events are expected to rise in the future and increase the related health risks of human beings. Using a novel, nationwide dataset that links extreme temperature and mortality, we estimated the short-term and long-term effects of extreme temperature on mortality in China during 2002-2013. Both extreme hot and extreme cold had immediate and long-term effects on all-cause mortality. Annual deaths per 100,000 people due to extreme hot and cold in the long term were considerably larger compared to the short term. The change in cold spell duration indicator exhibited the greatest effects on annual deaths per 100,000 people among a set of extreme weather indicators. Furthermore, cities with low economic development levels were more vulnerable to extreme temperature, compared to cities with high economic development levels. Our results offer important policy implications for developing a regional-specific extreme weather plan to handle extreme temperature events in China. [ABSTRACT FROM AUTHOR]

A set of homogenized monthly mean surface air temperature (SAT) series at 32 stations in China back to the 19th century had previously been developed based on the RHtest method by Cao et al., but some inhomogeneities remained in the dataset. The present study produces a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization (MASH) method. The MASH procedure detects 33 monthly temperature records as erroneous outliers and 152 meaningful break points in the monthly SAT series since 1924 at 28 stations. The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series. The new data show significant warming trends during 1924-2016 at all the stations, ranging from 0.48 to 3.57°C (100 yr)−1, with a regional mean trend of 1.65°C (100 yr)−1; whereas, the previous results ranged from a slight cooling at two stations to considerable warming, up to 4.5°C (100 yr)−1. It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century. The new data are available online at http://www.dx.doi.org/10.11922/sciencedb.516. [ABSTRACT FROM AUTHOR]

Climate plays an important role in heating energy consumption owing to the direct relationship between space heating and changes in meteorological conditions. To quantify the impact, the Transient System Simulation Program software was used to simulate the heating loads of office buildings in Harbin, Tianjin, and Shanghai, representing three major climate zones (i.e., severe cold, cold, and hot summer and cold winter climate zones) in China during 1961-2010. Stepwise multiple linear regression was performed to determine the key climatic parameters influencing heating energy consumption. The results showed that dry bulb temperature (DBT) is the dominant climatic parameter affecting building heating loads in all three climate zones across China during the heating period at daily, monthly, and yearly scales (R2 ≥ 0.86). With the continuous warming climate in winter over the past 50 years, heating loads decreased by 14.2, 7.2, and 7.1 W/m2 in Harbin, Tianjin, and Shanghai, respectively, indicating that the decreasing rate is more apparent in severe cold climate zone. When the DBT increases by 1 °C, the heating loads decrease by 253.1 W/m2 in Harbin, 177.2 W/m2 in Tianjin, and 126.4 W/m2 in Shanghai. These results suggest that the heating energy consumption can be well predicted by the regression models at different temporal scales in different climate conditions owing to the high determination coefficients. In addition, a greater decrease in heating energy consumption in northern severe cold and cold climate zones may efficiently promote the energy saving in these areas with high energy consumption for heating. Particularly, the likely future increase in temperatures should be considered in improving building energy efficiency. [ABSTRACT FROM AUTHOR]

China's climate change policy has rapidly evolved from one of neglect to necessity with sinologists drawing on a wide range of theories in trying to explain this shift. The rising influence of citizens' movements coupled with international pressure are often cited as significant drivers behind the government's evolving climate change strategy. But can the influence of public pressure and international lobbying offer a complete explanation for the government's dramatic policy changes? In this article, we advance theoretical pluralism where three contending schools of thought are made complementary to offer distinct explanations for understanding the mechanisms and rationale for Beijing's elite-driven climate change policy. In brief, by bridging three separate theoretical streams including rational choice theory, authoritarian environmentalism and advocacy coalition framework, we show that the interests of elites in China's upper political echelon are the driving force behind the country's climate change policy. [ABSTRACT FROM AUTHOR]

Impacts of climate variability and climate change are on the rise in China posing great threat to agriculture and rural livelihoods. Consequently, China is undertaking research to find solutions of confronting climate change and variability. However, most studies of climate change and variability in China largely fail to address farmers' perceptions of climate variability and adaptation. Yet, without an understanding of farmers' perceptions, strategies are unlikely to be effective. We conducted questionnaire surveys of farmers in two farming regions, Yifeng, Jiangsu and Qinxi, Anhui achieving 280 and 293 responses, respectively. Additionally, we used climatological data to corroborate the farmers' perceptions of climate variability. We found that farmers' were aware of climate variability such that were consistent with climate records. However, perceived impacts of climate variability differed between the two regions and were influenced by farmers' characteristics. In addition, the vast majorities of farmers were yet to make adjustments in their farming practices as a result of numerous challenges. These challenges included socioeconomic and socio-cultural barriers. Results of logit modeling showed that farmers are more likely to adapt to climate variability if contact with extension services, frequency of seeking information, household heads' education, and climate variability perceptions are improved. These results suggest the need for policy makers to understand farmers' perceptions of climate variability and change in order to formulate policies that foster adaptation, and ultimately protect China's agricultural assets. [ABSTRACT FROM AUTHOR]

Advance in spring plant phenology over the last several decades has been found in all continents of the Northern Hemisphere. Compared to the studies detecting phenological trends, the studies investigating the geographical pattern of phenological variability (including mean date and magnitude of variability) are rather limited. In this study, we analyzed spatial pattern of mean date and standard deviation (SD) of first bloom date (FBD) time series (≥15 years) for black locust ( Robinia pseudoacacia) at 22 stations in China, common lilac ( Syringa vulgaris) at 79 stations in the Western US and Chinese lilac ( Syringa chinensis) at 45 stations in the Eastern US. Subsequently, the impact of geographical factors (latitude, longitude, and altitude) on the mean date and SD was quantified by using the multiple regression analysis method. Meanwhile, the relationship between FBD variability and temperature sensitivity of FBD was examined. Results showed that the mean FBD highly depended on geographical factors for all the three species. Compared to the mean date, the dependence of SD of FBD time series on geographical factors was weaker. The geographical factors could only explain 13 to 31 % of spatial variance in SD of FBD. The negative regression coefficients of latitude ( P < 0.05 except black locust) indicated that FBD is more variable at lower latitude. At most of stations, significant and negative correlations between FBD and preseason temperature on interannual scale were found, but the temperature sensitivity varied among different stations. The magnitude of temperature sensitivity decreased with increasing latitude. In general, the locations at lower latitude had earlier and more variable spring phenophase and showed stronger phenological response to climate change than the locations at higher latitude. [ABSTRACT FROM AUTHOR]

Agricultural production is a complex interaction between human and natural environment, making agriculture both significantly responsible and vulnerable to climate change. China, whose socioeconomy is fundamentally dependent on agriculture, is already experiencing climate-change-related issues that threaten food security and sustainable development. Climate change mitigation and adaptation are of great concern to ensure food security for the growing population and improve the livelihoods of poor smallholder producers. A questionnaire survey was conducted in Henan Province, China to assess agronomic practices of smallholder farmers, adaptation strategies and how climate change awareness and perceptions influence the farmers' choice of agronomic practices. The results showed that the vast majority of farmers owned <10 Chinese Mu (0.7 ha) and nearly all farmers' relied on intensive use of chemical fertilizers and pesticides to increase yield at the detriment of environment. However, farmers who were aware of climate change had adopted agronomic practices that reduce impacts of climate change. Information about climate change, lack of incentives, lack of credit facilities and small farm sizes were major hindrance to adaptation and adoption of farming practices that can reduce impacts of climate change. This study recommends that research findings should be disseminated to farmers in timely and appropriate ways. The central government should formulate policies to include subsidies and incentives for farmers to motivate adoption of eco-friendly agronomic practices. [ABSTRACT FROM AUTHOR]

Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5) models, climatic extremes and their changes over China in the past and under the future scenarios of three Representative Concentration Pathways (RCPs) are analyzed. In observations, frost days (FD) and low-temperature threshold days (TN10P) show a decreasing trend, and summer days (SU), high-temperature threshold days (TX90P), heavy precipitation days (R20), and the contribution of heavy precipitation days (P95T) show an increasing trend. Most models are able to simulate the main characteristics of most extreme indices. In particular, the mean FD and TX90P are reproduced the best, and the basic trends of FD, TN10P, SU and TX90P are represented. For the FD and SU indexes, most models show good ability in capturing the spatial differences between the mean state of the periods 1986-2005 and 1961-80; however, for other indices, the simulation abilities for spatial disparity are less satisfactory and need to be improved. Under the high emissions scenario of RCP8.5, the century-scale linear changes of the multi-model ensemble (MME) for FD, SU, TN10P, TX90P, R20 and P95T are −46.9, 46.0, −27.1, 175.4, and 2.9 days, and 9.9%, respectively; and the spatial change scope for each index is consistent with the emissions intensity. Due to the complexities of physical process parameterizations and the limitation of forcing data, great uncertainty still exists with respect to the simulation of climatic extremes. [ABSTRACT FROM AUTHOR]

To address the increasing hazards of climate change to winter oilseed rape production in Jiangsu province, southeast China, a total of 12 agro-meteorological disaster indices (MDI) during 1961–2012 was applied to quantify the disaster impacts of spring precipitation extremes, autumn droughts, winter freezing injuries, and spring chilling injuries. The main findings were as follows: (1) due to the obvious north-south gradient of MDI, this province was classified as four climactic sub-regions: north, central-north, central-south, and south Jiangsu, respectively; (2) in central-north, central-south, and south Jiangsu, the maximum length of dry spell during autumn (DI3), the maximum duration of consecutive rainfalls during spring (PI3), and number of rainy days during spring (PI1) were selected as the leading MDI affecting oilseed rape yield, respectively; (3) each 1d of DI3, PI3, and PI1 increase would result in yield losses of 0.7%, 3.6%, and 1.7% in central-north, central-south, and south Jiangsu, respectively; (4) compared to the weak changes in spring rainfall and autumn drought, the significant weakening of winter-spring cold extremes across Jiangsu had more notable yield increasing effects, especially the strong decrease of freezing events during winter had increased yield by up to 1.4–3.0%. [ABSTRACT FROM AUTHOR]