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Based on the annual average climate data and economic and social data from 262 prefecture-level cities in China from 2001 to 2019, this paper explores the impact of climate change on urban–rural income inequality and its mechanisms using fixed-effects (FEs) and mediated-effects (MEs) models. This study finds that (1) climate change has an inverted U-shaped relationship with the urban–rural income disparity; (2) climate change can affect the urban–rural income disparity by influencing urban and rural income levels, the regional degree of urbanization, and the labor force employment structure; (3) the impact of climate change on the urban–rural income gap is heterogeneous in East, Center, and West China; and (4) extreme heat can widen the urban–rural income gap, and extreme drought can narrow the urban–rural income gap. Climate change has a significant impact on the urban–rural income gap, and there is a need to continue to promote urbanization and the optimization of the employment structure of the workforce, reduce the vulnerability of rural residents to climate change, and narrow the urban–rural income gap. [ABSTRACT FROM AUTHOR]

Climate change is having a significant impact on farmers and agriculture. Rising temperatures and extreme weather events, such as droughts and floods, are causing crop failures and reducing yields. This study evaluated existing publications from 2006 to 2022, using the Web of Science database, Citespace, and the Bibliometrix package in R language for a systematic analysis. A total of 426 publications were identified, written by 1449 authors from 56 countries. The results showed that China has the highest share of publications (16.4%), followed by the United States (14.3%) and Australia (6.8%), with China and Pakistan collaborating most frequently. The keyword timeline analysis from 2006 to 2022 identified 11 clusters of research topics related to farmers' climate change risk (CCRF). Cluster #1, "water conservation measures," had the longest duration, highlighting its significance. Key areas of CCRF research include the vulnerability of land-lost farmers, farmers' use of meteorological information, sources of risk, barriers to implementing conservation agriculture, farmers' attitudes towards heavy metal pollution, and the use of protection motivation theory in agricultural adaptation. In conclusion, climate change poses significant threats to farmers, impacting crop yields, soil fertility, and water availability. Farmers adopt adaptation strategies, but effectiveness varies due to resource limitations and policy gaps. The research on farmer adaptation to climate change is growing, emphasizing the need for supportive policies, resources, and knowledge-sharing to achieve sustainable agriculture and food security. [ABSTRACT FROM AUTHOR]

The agro-pastoral transitional zone in northern China is an important agricultural and pastoral production base. This study focuses on the eastern section of the agro-pastoral transitional zone in northern China. Combined with spatio-temporal analysis, stepwise regression, and gray relation analysis, we analyzed the average annual growth rate, spatio-temporal changes, and influencing factors of agricultural and pastoral production in the study area during 2000–2020. The results show that, in the past 20 years, the agricultural and pastoral production of the 50 municipal districts and counties has significantly changed, among which the agricultural production of 38 municipal districts and counties has shown an extremely significant increase. Generally, the growth rate of agricultural production is higher than that of pastoral production. Agricultural and pastoral production in the study area is influenced by socio-economic and land use/cover factors, with an average correlation degree of 0.79 and 0.88, respectively. Climate change affects agricultural production in agricultural counties, with a correlation degree of 0.85. The results of this research provide valuable insights into understanding the long-term temporal and spatial changes in agricultural and pastoral production and help to develop sound agriculture and pastoral management practices in the eastern section of the agro-pastoral transitional zone in Northern China. [ABSTRACT FROM AUTHOR]

Cold chain logistics are crucial for reducing agricultural product loss, yet the environmental impact of energy and packaging consumption, among others, demands attention, making the search for eco-friendly development modes essential. Based on data from 30 provinces in China from 2015 to 2021, this study analyzes the basic correlation between the development of cold chain logistics of fresh agricultural products (CCLFAP) and the ecological environment (EE) by using a random forest regression model in comparison with the XGBoost model. Correlation heatmaps were used to analyze the relationships between the cold chain logistics of fresh agricultural products and various factors of the ecological environment. The generalized additive model was then used to establish the connection between cold chain logistics and the ecological environment, identifying significant factors impacting EE. The results demonstrate that a higher development level of cold chain logistics corresponds to a better development trend of EE. The economic efficiency and technical aspects of cold chain logistics for fresh agricultural products are closely related to ecological pressures and responses. The number of employees in the logistics industry, the trading volume of fresh agricultural products, the number of refrigerated vehicles, and the capacity of the cold room have significant positive correlations with the ecological environment, while the per capita consumption of fresh agricultural products, the number of cold chain logistics patent applications, and the road density had significant negative correlations with the ecological environment. The effects of the number of cold chain logistics enterprises and the freight turnover of agricultural products transported by the cold chain on the ecological environment fluctuated. These findings contribute to reducing climate and environmental emergencies throughout the life cycle, offering sustainable development solutions for the fresh agricultural product cold chain logistics industry. [ABSTRACT FROM AUTHOR]

Extreme climate events frequently have more severe effects on terrestrial vegetation activity than long-term changes in climate averages. However, changes in extreme climate events as well as their potential risk on vegetation activity are still poorly understood. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper aims to understand the vegetation response to changes in extreme precipitation events from 1982 to 2012 using the maximum normalized difference vegetation index (NDVI) as an indicator. By applying extreme value theory (EVT), the potential risks of extreme precipitation events on vegetation activity were analyzed by conducting return period analysis. Results indicated that vegetation activity could be affected by extreme precipitation events, especially the combined effects of the frequency and intensity of precipitation extremes. For instance, vegetation activity could be enhanced in the regions with weakened intensity but increased occurrence of extreme precipitation events. In addition, we found potential risk of extreme precipitation events on vegetation activity from the results of precipitation extreme trend and return period analysis. These phenomena can be associated with the local occurrence of extreme precipitation events, different land cover types, and soil moisture cumulative effect on vegetation growth. This study stresses the importance of considering both current changes in and the potential risk of extreme precipitation events to understand their effects on vegetation activity. [ABSTRACT FROM AUTHOR]

This study evaluates how resilient farmers' livelihoods are to climate change and what factors influence this resilience. To measure resilience, we constructed an indicator system based on the livelihood resilience analysis framework. We surveyed 42 experts and 630 farmers after a climate change disturbance in Aohan Banner, Inner Mongolia, from August to October 2021, and analyzed these data using the comprehensive index method. Meanwhile, we used a multiple linear regression model to analyze the key factors affecting farmer livelihood resilience across different livelihood types and towns. We found that farmers who primarily worked in agriculture had the highest resilience scores and that livelihood resilience differed by geographical location; specifically, livelihood resilience gradually declines from southern to northern areas and from forest and forest-grassland to grassland locations. The results also show that education level, agricultural technology training, transportation infrastructure, accessibility of information, awareness of climate change, climate change perception, change in livelihood strategies, family size, and the holding size of the arable area are positively associated with farmer livelihood resilience, while household head age is negatively associated with resilience. We therefore advise that policymakers should diversify agricultural livelihoods, afforest surrounding arable areas, improve transportation infrastructure, increase learning activities and skill training for farmers, and publicize climate change knowledge. [ABSTRACT FROM AUTHOR]

Climate change has dramatic impacts on the growth and the geographical distribution of tea (Camellia sinensis L.). Assessing the potential distribution of tea will help decision makers to formulate appropriate adaptation measures to use the altered climatic resources and avoid the damage from climate hazards. The objective in this study is to model the current and future distribution of tea species based on the four SSPs scenarios using the MaxEnt model in China. For the modeling procedure, tea growth records in 410 sites and 9 climate variables were used in this paper. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the model. The AUC value was over 0.9 in this study, showing the excellent simulation result of the model. In relation to the current distribution, areas of 82.01 × 104 km2 (8.51% of total land area in China), 115.97 × 104 km2 (12.03% of total land area in China), and 67.14 × 104 km2 (6.97% of total land area in China) were recognized as Marginal, Medium, and Optimal climate suitable habitats for tea over China. Compared to the current distribution, most of the Optimal suitability areas in southeast China would be lost in four scenarios. The area of Marginal and Medium suitable habitats would expand in SSP370 and SSP585, especially in 2041–2061 and 2081–2100. The suitable area of tea would expand northwards and westwards, suggesting that additional new suitable habitats could be created for tea production with the future climate change, especially in Shandong, Henan, Guizhou, and Yunnan Provinces. This research would provide vital scientific understanding for policy making on tea production, tea garden site chosen and adopyion of adaptation methods in the future. [ABSTRACT FROM AUTHOR]

Chlorpyrifos has been used extensively for decades to control crop pests and disease-transmitting insects; its contribution to increasing food security and minimizing the spread of diseases has been well documented. Pymetrozine and Avermectin (also known as abamectin) have been used to replace the toxic organophosphate insecticides (e.g., Chlorpyrifos) applied to rice crops in China, where the overuse of pesticides has occurred. In addition, climate change has exacerbated pesticide use and pollution. Thus, farmers and communities are at risk of exposure to pesticide pollution. This study reviews the contamination, exposure, and health risks through environmental and biological monitoring of the legacy pesticide Chlorpyrifos and currently used insecticides Pymetrozine and Avermectin in China; it investigates whether changes in pesticide usage from Chlorpyrifos to Pymetrozine and Avermectin reduce pesticide contamination and health hazards to communities and residents. In addition, this review discusses whether Pymetrozine and Avermectin applications could be recommended in other countries where farmers largely use Chlorpyrifos and are exposed to high health risks under climate change scenarios. Although Chlorpyrifos is now banned in China, farmers and residents exposed to Chlorpyrifos are still experiencing adverse health effects. Local farmers still consider Chlorpyrifos an effective pesticide and continue to use it illegally in some areas. As a result, the concentration levels of Chlorpyrifos still exceed risk-based thresholds, and the occurrence of Chlorpyrifos with high toxicity in multiple environmental routes causes serious health effects owing to its long-term and wide application. The bioaccumulation of the currently used insecticides Pymetrozine and Avermectin in the environment is unlikely. Pymetrozine and Avermectin used in paddy water and soil for crop growth do not pose a significant hazard to public health. A change in pesticide use from Chlorpyrifos to Pymetrozine and Avermectin can reduce the pesticide contamination of the environment and health hazards to communities and residents. Finally, we recommend Pymetrozine and Avermectin in other countries, such as Vietnam, and countries in Africa, such as Ghana, where farmers still largely use Chlorpyrifos. [ABSTRACT FROM AUTHOR]

Global warming has become one of the major threats to the security of human survival, security, and sustainable development. Agricultural production has been widely suspected as one of the main sources of anthropogenic carbon emissions. Analyzing the changing characteristics and influencing factors of agricultural carbon emissions is of great significance for the mitigation of global climate change and the sustainable development in agriculture. Taking China, a large agricultural country, as an example, this study used the empirical model to quantify carbon emissions from agricultural inputs from 1991 to 2019, and analyzed the driving factors using ridge regression. We found that agricultural carbon emissions in China have been on the rise in the past 30 years, but at a markedly slower pace. From 2008 to 2019, the average annual growth rate of agricultural carbon emissions was 1.47%, down significantly from 2.92% between 1991 and 2007. The carbon emissions per unit of planting area showed an overall increasing trend, which grew from 179.35 t ce/km2 to 246.26 t ce/km2, with an average annual growth rate of 1.13%. The carbon emissions per unit of agricultural output mainly showed a decreasing trend, which decreased from 0.52 kg ce/CNY to 0.06 kg ce/CNY, with an average annual rate of change of −7.42%. China's agricultural carbon emissions were closely related to macro-policies. Fertilizer inputs, agricultural industry structure, and energy use intensity were significantly positively correlated with carbon emission intensity. The degree of urban feedback to rural areas, public investment in agriculture, and large-scale planting were significantly negatively correlated with carbon emission intensity, but the impacts of these factors had a "lag effect". In order to reduce carbon emissions from agriculture and promote development in green agriculture, we suggest that the government should further increase the degree of urban feedback to rural and public investment in the agricultural sector. In addition, large-scale agricultural production should be encouraged to increase resource efficiency and reduce carbon emissions. [ABSTRACT FROM AUTHOR]

The global warming phenomenon has undoubtedly brought unprecedented challenges to rice production, vital for food security in Southeast Asian countries and China. Most studies on this topic have focused narrowly on the direct effect of climate change on rice yield, neglecting the indirect effect. Using panel data from 30 provinces in China from 1990 to 2016, in this paper, we propose and test a mediational effect model to examine the mechanisms of how climate change affects rice yield. We find that climate change leads to changes in functional irrigation areas, farmers' fertilizing behavior, and agricultural labor supply, and it is these mediating factors that effectively transmit the impact of climate change to China's rice production. The positive indirect impact of climate change on the factors of production often partially or overly compensates for the adverse direct effect of climate change on rice yield, leading to a surprising observation of the association of climate change with increased rice yield, at least in the short run. We also provide some preliminary policy advice based on the analysis. [ABSTRACT FROM AUTHOR]

As a globally important sugarcane-producing region, Southern China (SC) is severely affected by various agrometeorological disasters. This study aimed to comprehensively assess multiple sugarcane agrometeorological disasters with regards to sugarcane yield in SC. The standardized precipitation evapotranspiration index and the heat degree-days were employed to characterize drought, flood, and high temperature (HT) during sugarcane growth stages in three provinces in SC in the period 1970–2020. Moreover, the relationships between sugarcane climatic yield and disaster intensities were investigated. The results indicated that the most recent decade witnessed the most intensive sugarcane agrometeorological disasters; sugarcane drought and HT intensities significantly (p < 0.05) increased in one and two provinces, respectively. Central and western SC was most drought-prone, while eastern SC was most flood-prone; sugarcane HT was concentrated in southwestern SC. The mature stage exhibited the greatest monthly intensities of drought and flood; the most HT-prone growth stage varied with provinces. The relationships between drought/flood intensity and sugarcane climatic yield were significant in seven districts; the yield-reducing effect of sugarcane flood was more obvious than that of drought. In conclusion, this study provides references for agrometeorological disaster risk reduction for sugarcane in SC. [ABSTRACT FROM AUTHOR]

Efficient utilization of light and heat resources is an important part of cleaner production. However, exploring the changes in light and heat resources utilization potential in paddy under future climate change is essential to make full use of the potential of rice varieties and ensure high-efficient, high-yield, and high-quality rice production, which has been seldom conducted. In our study, a process-based crop model (CERES-Rice) was calibrated and validated based on experiment data from the Songnen Plain of China, and then driven by multiple global climate models (GCMs) from the coupled model inter-comparison project (CMIP6) to predict rice growth period, yield, and light and heat resources utilization efficiency under future climate change conditions. The results indicated that the rice growth period would be shortened, especially in the high emission scenario (SSP585), while rice yield would increase slightly under the low and medium emission scenarios (SSP126 and SSP245), it decreased significantly under the high emission scenario (SSP585) in the long term (the 2080s) relative to the baseline of 2000–2019. The light and temperature resources utilization (ERT), light utilization efficiency (ER), and heat utilization efficiency (HUE) were selected as the light and heat resources utilization evaluation indexes. Compared with the base period, the mean ERT in the 2040s, 2060s, and 2080s were −6.46%, −6.01%, and −6.03% under SSP126, respectively. Under SSP245, the mean ERT were −7.89%, −8.41%, and −8.27%, respectively. Under SSP585, the mean ERT were −6.88%, −13.69%, and −28.84%, respectively. The ER would increase slightly, except for the 2080s under the high emission scenario. Moreover, the HUE would reduce as compared with the base period. The results of the analysis showed that the most significant meteorological factor affecting rice growth was temperature. Furthermore, under future climate conditions, optimizing the sowing date could make full use of climate resources to improve rice yield and light and heat resource utilization indexes, which is of great significance for agricultural cleaner production in the future. [ABSTRACT FROM AUTHOR]

This article scientifically studies the direct impact of climate problems on the time transition of reference crop evapotranspiration in the Xinjiang Autonomous Region of China from 1957 to 2017, which is conducive to formulating irrigation scheduling and adaptive capacity countermeasures. The objective of this study is to investigate the impacts of climate change on ETo for the cotton growing seasons. The meteorological data were collected from 48 meteorological stations in the region and analyzed using the Mann–Kendall test and linear trend. The results show the following points: (1) the ETo decreases from low to high elevations, and with the increase in northern latitude. (2) The annual mean ETo and average values of ETo during the growing seasons for cotton exhibited two abrupt changes in the period 1957–2017, with the first abrupt change in 1995 to 1999 and the second abrupt change in 2006 to 2011. (3) The ETo in Xinjiang of China demonstrates a decreasing trend during 1957–1996; a significant decreasing trend during 1997–2008; and a significant increasing trend during 2009–2017. [ABSTRACT FROM AUTHOR]

Understanding future changes in water supply and requirement under climate change is of great significance for long-term water resource management and agricultural planning. In this study, daily minimum temperature (Tmin), maximum temperature (Tmax), solar radiation (Rad), and precipitation for 26 meteorological stations under RCP4.5 and RCP8.5 of MIRCO5 for the future period 2021–2080 were downscaled by the LARS-WG model, daily average relative humidity (RH) was estimated using the method recommended by FAO-56, and reference crop evapotranspiration (ET0), crop water requirement (ETc), irrigation water requirement (Ir), effective precipitation (Pe), and coupling degree of ETc and Pe (CD) for soybean during the growth period were calculated by the CROPWAT model in Heilongjiang Province, China. The spatial and temporal distribution of these variables and meteorological factors were analyzed, and the response of soybean water supply and requirement to climate change was explored. The result showed that the average Tmin, Tmax, and Rad under RCP4.5 and RCP8.5 increased by 0.2656 and 0.5368 °C, 0.3509 and 0.5897 °C, and 0.0830 and 0.0465 MJ/m², respectively, while the average RH decreased by 0.0920% and 0.0870% per decade from 2021 to 2080. The annual average ET0, ETc, Pe, and Ir under RCP4.5 for 2021–2080 were 542.89, 414.35, 354.10, and 102.44 mm, respectively, and they increased by 1.92%, 1.64%, 2.33%, and −2.12% under the RCP8.5, respectively. The ranges of CD under RCP4.5 and RCP8.5 were 0.66–0.95 and 0.66–0.96, respectively, with an average value of 0.84 for 2021–2080. Spatially, the CD showed a general trend of increasing first and then decreasing from west to east. In addition, ET0, ETc, and Pe increased by 9.55, 7.16, and 8.77 mm per decade, respectively, under RCP8.5, while Ir decreased by 0.65 mm per decade. Under RCP4.5 and RCP8.5, ETc, Pe, and Ir showed an overall increasing trend from 2021 to 2080. This study provides a basis for water resources management policy in Heilongjiang Province, China. [ABSTRACT FROM AUTHOR]

Climate change has and will continue to exert significant effects on social economy, natural environment, and human life. Research on the climatic suitability of crops is critical for mitigating and adapting to the negative impacts of climate change on crop production. In the study, we developed the climate suitability model of maize and investigated the climate suitability of summer maize during the base period (1981–2010) and two future periods of 2031–2060 (2040s) and 2071–2100 (2080s) in the North China Plain (NCP) based on BCC-CSM2-MR model (BCC) from the Coupled Model Comparison Program (CMIP6) under two Shared Socioeconomic Pathways (SSP) 245 and SSP585. The phenological shift of maize under future climate scenarios was simulated by the Agricultural Production Systems Simulator (APSIM). The results showed that the root mean square errors (RMSE) between observations and projections for sunshine suitability (SS), temperature suitability (ST), precipitation suitability (SP), and integrated climate suitability (SZ) during the whole growth period were 0.069, 0.072, 0.057, and 0.040, respectively. Overall, the BCC projections for climate suitability were in suitable consistency with the observations in the NCP. During 1981–2010, the SP, ST, and SZ were high in the north of the NCP and low in the south. The SP, ST, and SZ showed a downward trend under all the future climate scenarios in most areas of NCP while the SS increased. Therein, the change range of SP and SS was 0–0.1 under all the future climate scenarios. The ST declined by 0.1–0.2 in the future except for the decrease of more than 0.3 under the SSP585 scenario in the 2080s. The decrease in SZ in the 2040s and 2080s under both SSP scenarios varied from 0 to 0.2. Moreover, the optimum area decreases greatly under future scenarios while the suitable area increases significantly. Adjusting sowing data (SD) would have essential impacts on climate suitability. To some extent, delaying SD was beneficial to improve the climate suitability of summer maize in the NCP, especially under the SSP585 scenario in the 2080s. Our findings can not only provide data support for summer maize production to adapt to climate change but also help to propose agricultural management measures to cope with future climate change. [ABSTRACT FROM AUTHOR]

Hainan Island is endowed with unique climatic and geographical conditions in China. Green orange is a characteristic fruit and plays an important role in local agricultural production of the island. However, few studies have been available regarding the climatic suitability index of green orange planting suitable regions in the island. Based on 30 years (1980 to 2019) of climatic data from 19 meteorological stations in the island, this study established spatial analysis models with topographical data, land use and GIS spatial analysis. Based on climate suitability function, this study established the climate suitability models of temperature, sunshine, precipitation, accumulated temperature and comprehensive suitability model for green orange planting. The Climate suitability index model for green orange planting suitable zoning areas was developed using a natural point segmentation method, and future climate change scenarios were adopted for evaluating the trends of climate suitable areas. The results revealed that the most suitable areas for planting green orange are mainly located at the eastern central region in the island. The climate suitability index ranged from 0.9 to 1.0 in the most suitable regions. The suitable area is mainly distributed in the eastern part, most of the central and western parts of the island, with the climate suitability index ranging from 0.7–0.9. However, the population density in the area is large, and the planting land is limited. The sub-suitable area is mainly located in the coastal areas of the western island, and the high-altitude areas in the central and western regions of the island, with the climate suitability index varying from 0.4 to 0.7. The unsuitable area is mainly distributed in the central mountainous area, with the climate suitability index being 0.0–0.4. The suitability of temperature showed decreasing trend, and the suitability of precipitation gradually moved from the east to the central region under future climate change scenarios. This study is helpful in promoting the development and utilization of agricultural resources and the fine zoning of green orange planting climate suitability in the island. [ABSTRACT FROM AUTHOR]

Climate change and farmland environmental pollution have put greater pressure on the sustainability of agricultural production. Based on the provincial panel data of mainland China from 1978 to 2018, climate variables such as precipitation, temperature, and sunshine hours are included into the input indicators, and agricultural non-point source pollution and carbon emissions are taken as undesirable outputs, the agricultural production efficiency (APE) under the dual constraints of climate change and the resource environment was estimated by the super slacks-based measure (SBM)-undesirable model. On the basis of the trajectory of the imbalanced spatiotemporal evolution of APE shown by Kernel density estimation and the standard deviational ellipse (SDE)–center of gravity (COG) transfer model, the spatial convergence model was used to test the convergence and differentiation characteristics of APE. Under the dual constraints, APE presents a "bimodal" distribution with a stable increase in fluctuation, but it is still at a generally low level and does not show polarization, among which the APE in the northeast region is the highest. The COG of APE tends to transfer towards the northeast, and the coverage of the SDE is shrinking, so the overall spatial pattern is characterized by a tendency of clustering towards the north in the north-south direction and a tendency of imbalance in the east-west direction. APE has significant spatial convergence, and there is a trend of "latecomer catching-up" in low-efficiency regions. The introduction of spatial correlation accelerates the convergence rate and shortens the convergence period. The convergence rate is the highest in the central and western regions, followed by that in the northeastern region, and the convergence rate is the lowest in the eastern region. In addition, the convergence rate in different time periods has a phase change. The process of improving the quality and efficiency of agricultural production requires enhancing the adaptability of climate change, balancing the carrying capacity of the resource environment, and strengthening inter-regional cooperation and linkage in the field of agriculture. [ABSTRACT FROM AUTHOR]

With the extreme changes of the global climate, winter freezing injury has become an important limiting factor for the development of the global grape industry. Therefore, there is a significant need for the screening of cold-resistant wine grape germplasms and cold regionalization for cold-resistant breeding and the development of grapevine cultivation in cold regions. In this study, the low-temperature half-lethal temperature (LT50) values were determined for the annual dormant branches of 124 wine grape germplasms (V. vinifera) to evaluate their cold resistance. The LT50 values of the 124 tested germplasms ranged from −22.01 °C to −13.18 °C, with six cold-resistant germplasms below −20 °C. Based on the LT50 values, the 124 germplasms were clustered into four types, with cold resistance from strong to weak in the order of type Ⅱ > type Ⅰ > type Ⅳ > type Ⅲ, corresponding to the four cold hardiness zones. Zones 1, 2, 3, and 4 included 6, 22, 68, and 28 germplasms, respectively, with decreasing cold resistance. The number of germplasms in different hardiness zones followed a normal distribution, with the most in zone 3. In Type Ⅱ, the fruit skin color of germplasms was positively correlated with cold hardiness, while the temperature of origin was negatively correlated with cold hardiness. The average LT50 of germplasms in different origin regions ranged from −17.44 °C to −16.26 °C, with differences among some regions. The cold regionalization analysis resulted in the distribution of 124 germplasms in four temperature regions in China with six germplasms in region A (−22 °C ≤ LT50 ≤ −20 °C), 30 germplasms in region B (−20°C ≤ LT50 ≤ −18°C), 71 germplasms in region C (−18 °C ≤ LT50 ≤ −15 °C), and 17 germplasms in region D (−15 °C ≤ LT50 ≤ −13 °C). Strong cold-resistant wine grape germplasms (V. vinifera) were identified, and these could be used as parental material for cold-resistant breeding. In some areas in China, soil-burial over-wintering strategies are used, but our results suggest that some wine grapes could be cultivated without requiring winter burial during overwintering. The results of this study should provide guidance for the selection of promising strains for cold-resistant breeding for expanded cultivation of improved varieties for wine grape production in China. [ABSTRACT FROM AUTHOR]

The intensification of global climate change leads to frequent mountain torrents, landslides, debris flows and other disasters, which seriously threaten the safety of residents' lives and property. However, few studies have compared and analyzed the livelihood vulnerability and adaptation strategies of farmers in different disaster-threatened areas under the background of climate change. Based on survey data of 327 households in the areas threatened by mountain floods, landslides and debris flow in Sichuan Province, this study analyzed the characteristics of livelihood vulnerability and adaptation strategies of households in the areas threatened by different disaster types and constructed multinomial logistic regression models to explore their correlations. The findings show that: (1) The livelihood vulnerability indices of farmers in different hazard types showed different characteristics. Among them, the livelihood vulnerability index of farmers in landslide-threatened zones is the highest, followed by the livelihood vulnerability index of farmers in debris-flow-threatened zones, and finally the livelihood vulnerability index of farmers in flash flood threat zones. At the same time, all three natural hazards show a trend of higher vulnerability in the sensitivity dimension than in the exposure and livelihood resilience dimensions. (2) The nonfarming livelihood strategy is the main livelihood strategy for farmers in different disaster-type-threatened areas. At the same time, the vulnerability of farmers choosing the nonfarming livelihood strategy is much higher than that of farmers choosing the part-time livelihood strategy and pure farming livelihood strategy, and the vulnerability of sensitivity dimension is higher than that of the exposure dimension and livelihood resilience dimension. (3) For farmers in landslide- and debris-flow-threatened areas, livelihood resilience is an important factor affecting their livelihood strategy. There was a positive correlation between livelihood resilience and farmers' choice of pure agricultural livelihood strategies in these two natural-disaster-threatened areas. This study deepens our understanding of the characteristics and relationships of farmers' livelihood vulnerability and adaptation strategies under different disaster types in the context of climate change, and then provides the reference basis for the formulation of livelihood-adaptive capacity promotion-related policy. [ABSTRACT FROM AUTHOR]

The presence of seasonal snow cover in the cold season can significantly affect the thermal conditions of the ground. Understanding the change of the snow–soil interface temperature (TSS) and its environmental impact factors is essential for predicting subnivean species changes and carbon balance in future climatic conditions. An improved Snow Thermal Model (SNTHERM) is employed to quantify TSS in farmland of Northeast China (NEC) in a 39-year period (1979–2018) firstly. This study also explored the variation tendency of TSS and its main influencing factors on grid scale. The result shows that annual average TSS and the difference between TSS and air temperature (TDSSA) increased rapidly between 1979 and 2018 in the farmland of NEC, and we used the Mann–Kendall test to further verify the increasing trends of TSS and TDSSA on aggregated farmland of NEC. The correlation analysis showed that mean snow depth (MSD) is the most pivotal control factor in 95% of pixels and TDSSA increases as MSD increases. Snow depth can better predict the change of TSS in deep–snow regions than average winter temperature (TSA). The results of this study are of great significance for understanding the impact of snow cover on the energy exchange between the ground and the atmosphere in the cold climate. [ABSTRACT FROM AUTHOR]

Tea is an important cash crop and a beverage that is widely consumed across the world. In China (the largest producer of tea), the industry is growing, and there is a need to understand current greenhouse gas (GHG) emissions and sequestrations and the potential for mitigation so that climate action can be strategically undertaken. Life cycle assessment and carbon footprint methods were used to quantify emissions in tea cultivation and processing in the 16 major producing regions for the year 2017. The system boundary was from cradle to factory gate, which was divided into three subsystems, namely agricultural materials production, tea production and tea processing. Several units of analysis were chosen: the production region (province), the production area (ha) and the product (kg loose tea), etc. Total GHG emissions were 28.75 Mt CO2eq, which were mainly attributable to energy use in tea processing (41%), fertilizer production (31.6%) and soil emissions (26.7%). This equated to 12.0 t CO2eq per ha and 10.8 kg CO2eq per kg processed tea. Production in Hubei, Yunan, Guizhou, Sichuan and Fujian provinces contributed almost two thirds of industry emissions, representing priority areas for strategic action to reduce GHG emissions. At the same time, the total carbon sink amounted to 21.37 MtCO2, representing 74.3% of total GHG emissions. The proportions stored in soil, biomass, and tea production were 49.3%, 30.0%, and 20.7%, respectively. If best recommended management practices for fertilizer application were adopted and biomass was used as a source of energy for tea processing, the GHG emissions reduction potential was 16.66 Mt CO2eq, or 58% of total emissions. The GHG emissions associated with tea production and processing in China appeared high by comparison to other regions of the world. However, considering the carbon sink and emissions reduction potential, the tea industry should be viewed as an important sector for climate action. Moreover, the potential for substantial GHG emissions reduction through the adoption of improved practices seems very realistic. There may also be additional opportunities for GHG emissions reduction through the development of organic tea cultivation systems. [ABSTRACT FROM AUTHOR]

Food security is considered as the most important global challenge. Therefore, identifying long-term drivers of food security and their connections is essential to steer policymakers determining policies for future food security and sustainable development. Given the complexity and uncertainty of multidimensional food security, quantifying the extent of uncertainty is vital. In this study, we investigated the uncertainty of a coupled hydrologic food security model to examine the impacts of climatic warming on food production (rice, cereal and wheat) in a mild temperature study site in China. In addition to varying temperature, our study also investigated the impacts of three CO2 emission scenarios—the Representative Concentration Pathway, RCP 4.5, RCP 6.0, RCP 8.5—on food production. Our ultimate objective was to quantify the uncertainty in a coupled hydrologic food security model and report the sources and timing of uncertainty under a warming climate using a coupled hydrologic food security model tested against observed food production years. Our study shows an overall increasing trend in rice, cereal and wheat production under a warming climate. Crop yield data from China are used to demonstrate the extent of uncertainty in food security modeling. An innovative and systemic approach is developed to quantify the uncertainty in food security modeling. Crop yield variability with the rising trend of temperature also demonstrates a new insight in quantifying uncertainty in food security modeling. [ABSTRACT FROM AUTHOR]