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Affected by global warming, the frequency of crop pests and diseases have increased, causing huge losses to agricultural production. To better grasp the development and trends of research on the effects of climate change on crop pests and diseases, the literature on the impact of climate change on crop pests and diseases published from 1990 to 2021 in the Web of Science (WOS) core collection database was used. This study explores the literature characteristics and hotspot evolution through the bibliometric visualization analysis software COOC, VOSviewer, and CiteSpace, with a view to identifying the changing characteristics and trends of research changes in this field. The results showed that the number of literature on the impact of climate change on crop pests and diseases increased rapidly. The main fields involved include environmental sciences, ecology, and agronomy. Papers in these fields mainly published in journals, such as PLos One, Forest Ecology and Management, and Frontiers in Plant Science. The country with the highest number of publications was the United States, followed by China and Australia. The most prolific authors in the top 20 are research scholars from China. The first author of the top 20 highly cited papers was from the United States. It was found that that current research on the impact of climate change on crop pests and diseases mainly focuses on agricultural production and food safety. Modelling and crop growth has maintained steady development. At present, research in this field mainly focuses on pest management strategies under the impact of climate change, the response of single species, and the complex ecological mechanisms behind the response. This study provides unique insights into the research field of the impact of climate change on crop pests and diseases and provides a reference direction for future research development in this field. [ABSTRACT FROM AUTHOR]

Tea (Camellia sinensis L.), as one of the most important cash crops in China, plays an important role in increasing farmers' incomes and guaranteeing a high quality of life. Tea production has been greatly influenced by both climate change and economic development in China. However, without a scientific understanding of the interaction mechanism of climate change and the impetus from rapid economic development on tea production practices in China, it is difficult to take adaptive actions to meet the climate change challenges for the tea industry. In this paper, we firstly assessed the potential impacts of climate change on tea climate suitability by empirical formula calculation using meteorological data; then, the effects from the additional climatic stress due to warming on tea production were detected with the annual statistical tea yield record on a municipal level. The contribution of socioeconomic development to the tea industry was evaluated with the comparison of the movement of China's national economy's and tea industry's gravity center during the period of 1987–2017. Finally, a conceptual adaptation framework was built to demonstrate the interaction mechanisms between climate change, tea production, and the economic development. The results showed that there was a negative impact of climate change on tea production in mainland China, with the percentage of high tea climate suitability (>0.9) areas dropping by 45% to 32%, while opportunities of enlarging the tea cultivating area emerged in the north tea production region where the tea climate suitability increased. We found that the tea planting area expanded northwards from 33° N in 1987 to 35° N in 2017 to take advantage of the favorable climatic resources due to warming, and tea planting decreased at an altitude of 100–400 m while increasing to higher altitude of 400–2000 m to avoid hot temperature damage and seek the optimum environment in high mountainous areas for tea production. In addition, the tea production moved westward along the longitude, decreasing obviously at 117–121° E while increasing significantly at 98–104° E and 107–110° E. Meanwhile, the tea production gravity center showed a westward movement consistent with the national economic gravity center moving trend, which means that tea industry development was driven by multiple socioeconomic factors and climatic forcings. A conceptual framework was built in this paper, aiming to show a robust adaptation mechanism for the tea system to maximize the benefits and minimize the damages from the altered climatic resources under rapid economic development in mainland China. The results in this study would help deepen the understanding of the adaptation process and practices for tea production in mainland China. [ABSTRACT FROM AUTHOR]

Iron isotope compositions, along with the partial extraction of iron in its various forms, can be utilized to investigate the complex interplay of iron migration and transformation with respect to iron isotope patterns. This study investigated the iron composition of a typical loess-paleosol sequence in Northeast China and aimed to understand the influence of iron migration and transformation of the typical loess-paleosol sequence on iron isotopes and environmental and climatic changes that occurred in the region over time by analyzing the distribution and characteristics of iron compositions in sedimentary layers. Samples were collected from Chaoyang in Northeast China, and the iron isotopic composition was analyzed using the multi-receiver inductively coupled plasma mass spectrometer (MC-ICP-MS). The findings revealed depth-dependent variations in the content of different iron forms, reflecting paleoclimatic shifts primarily through pedogenic transformation processes. Notably, iron migration within the section was observed to be limited. The variations in the reddening index and magnetic susceptibility of the loess-paleosol were primarily influenced by the presence of free iron (Fed), exhibiting a range of colors from yellow to red-yellow and red. The δ56Fe values for loess and paleosols ranged from 0.097 ± 0.035‰ to 0.167 ± 0.010‰, with an average of 0.133 ± 0.024‰ and a coefficient of variation (CV) of 15.66% at the stratum scale. These values indicated a systematic enrichment of heavy iron isotopes and a significant negative correlation with the slightly fluctuating total iron content. Specifically, our analysis highlighted distinct differences in δ56Fe values between paleosol (0.126 ± 0.024‰) and loess (0.146 ± 0.021‰). The δ56Fe in Fed was negative, averaging −0.101 ± 0.022‰, while the δ56Fe in silicate-bound iron was positive, averaging 0.156 ± 0.032‰. Intense pedogenesis, driven by warm and wet climates, facilitated iron transformations and migrations, resulting in the accumulation of light iron isotopes in the paleosols. These transformations and migrations were predominantly observed in microdomains characterized by iron depletions and concentrations, as reflected in the profile morphologies. However, the limited iron transformations and migrations did not result in significant Fe redistribution within the soil section, as evidenced by the limited variations in δ56Fe with soil depth at the stratum scale. Sampling from the stratum or pedogenic horizon could potentially create the illusion of the minimal fractionation of iron isotopes within the sequence. Therefore, a detailed examination of the iron isotope composition in the micro-domains of the loess-paleosol sequence is crucial to elucidate the fractionation processes and mechanisms of iron isotopes during the formation of these sequences. [ABSTRACT FROM AUTHOR]

Assessment of agricultural water requirements under future climate projections has received increasing attention in recent decades. The agriculture pattern of the semi-arid North China Plain is a maize–wheat rotation system in which sufficient irrigation is required to maintain production. In this study, the effects of future climate scenarios on the net irrigation requirement of the maize–wheat rotation system were assessed using the Food and Agriculture Organization crop growth model—AquaCrop. First, the baseline net irrigation requirement over the study region was obtained through AquaCrop simulation under ERA5-Land reanalysis from 2011 to 2020. In addition, the AquaCrop model was used to predict irrigation requirements in future scenarios (2021–2050) under the extreme-emission scenario of the Shared Socioeconomic Pathway SSP 5-8.5 (SSP 5-8.5). Finally, the predicted irrigation amount for maize and wheat during the period 2021–2050 under SSP 5-8.5 was compared with the baseline to assess the interannual change in irrigation water requirement. Results reveal significant agreement between the AquaCrop-derived daily soil moisture (SM) and a reference SM product with unbiased root mean square differences of 0.03 m3/m3 and 0.04 m3/m3 over maize and wheat, respectively. Furthermore, the median net irrigation requirement is expected to increase by approximately 107 mm (21%) to guarantee optimum yield. [ABSTRACT FROM AUTHOR]

Agroclimatic regionalization is an effective way to utilize agricultural climate resources in a reasonable manner. Accurate and objective agroclimatic regionalization plays a great directive role in ecological layout and decision support for agriculture farming. The purpose of this article was to investigate the influence of climate change on agroclimatic regions in China. Following the same regionalization principle concept as the theory and techniques of agroclimatic regionalization, three agroclimatic regions, the Tibetan High Cold Region (THCR), Northwest Arid Region (NAR), and Eastern Monsoon Region (EMR) were identified in China. The changes in the three agroclimatic regions were analyzed from 1961 to 2020 in the past and from 2006 to 2060 in the future. Future changes in agroclimatic regions were estimated from 2006 to 2030 and from 2031 to 2060 under scenarios RCP2.6, RCP4.5, and RCP8.5 for greenhouse gas emissions. The borders of agoclimatic regions had changed as a result of global climate warming and precipitation variability. There was a surplus in the geographical displacement and range of agroclimatic region borders in 1991 to 2020, especially when compared to those in 1961–1990. The TCHR exhibited significant spatial variation, with its northeast corner shifting nearly 170 km to the southwest. In the future, the area ratio of the THCR will be 26% by 2031–2060 under the RCP8.5 scenario, with the highest decline (1% compared to that in the reference period of 1981–2005), while under the RCP4.5 and RCP2.6 scenarios it will stabilize the area ratio at 27%. The eastern boundary of the NAR will migrate south or east, while the center boundary will rise northward. Under all three climatic scenarios, the area ratio will be 25% (down 1%). The range of the EMR will expand. The area ratio of the EMR will increase by 1% under the RCP2.6 and RCP4.5 scenarios and by 2% under the RCP8.5 scenario. Overall, our study may facilitate an in-depth understanding of agroclimatic regions changes and thus provide a scientific reference for the distribution of agricultural production and sustainable development under climate change in China. [ABSTRACT FROM AUTHOR]

The synchronicity of rain and heat in the summer of China's monsoon region provides sufficient water and heat resources for maize growth. However, the intra-annual distribution of precipitation and the probability of extreme precipitation have been inevitably altered by the ongoing climate change, thus affecting the matching degree between precipitation and crop water requirements (MDPCWR). Evaluating the extent to which the MDPCWR will change in the future is of great importance for food security and the sustainable management of water resources. In this study, considering that different growth stages of crops have different sensitivities to water stress, the AquaCrop model was used to calculate the MDPCWR more accurately. In addition, a cumulative distribution function-transform (CDF-t) method was used to remove the bias of 11 global climate models (GCMs) under two typical emission scenarios (SSP2-4.5 and SSP5-8.5) from phase six of the Coupled Model Intercomparison Project (CMIP6). A comprehensive investigation was conducted on how maize growth, water consumption, and the MDPCWR will respond to future climate change with CO2 concentration enrichment in the Huang–Huai–Hai (3H) region in China by driving a well-tested AquaCrop model with the bias-corrected GCMs outputs. The results indicate the following: (1) The CDF-t method can effectively remove seasonal bias, and it also performs well in eliminating the bias of extreme climate events. (2) Under the SSP2-4.5 scenario, the average maximum temperature will increase by 1.31 °C and 2.44 °C in 2021–2050 and 2051–2080, respectively. The average annual precipitation will increase up to 96.8 mm/year, but it will mainly occur in the form of heavy rain. (3) The increased maize evapotranspiration rate does not compensate for the decreased crop water requirement (up to −32 mm/year), due to a shorter growth cycle. (4) The farmland cultivation layer is not able to hold a significant amount of precipitation, due to the increased frequency of heavy rains, resulting in increased irrigation water requirements for maize over the next two periods, with the maximum value of 12 mm/year. (5) Under different scenarios, the projected future MDPCWR will decrease by 9.3–11.6% due to changes in precipitation patterns and crop water requirements, indicating that it will be more difficult for precipitation to meet the water demand of maize growing in the 3H region. The results can provide comprehensive information to understand the impact of climate change on the agricultural water balance and improve the regional strategy for water resource utilization in the 3H region. [ABSTRACT FROM AUTHOR]

Owing to limited research on the interactions between cropland vegetation and climate and irrigation, this study used the normalized difference vegetation index (NDVI) as a cropland vegetation indicator to describe vegetation dynamics. Potential evapotranspiration (PET) was calculated using the Penman–Monteith equation. A partial correlation analysis and a Pearson correlation coefficient were used to determine the spatial response mechanisms of cropland vegetation to different climatic factors and irrigation in China for the period 1985–2015. The results show that different climatic factors (precipitation, PET, and water deficits) display positive correlations with cropland vegetation in China. A stronger correlation was observed between cropland vegetation and meteorological factors in northern China compared to the southern parts; the response time of NDVI values of croplands to precipitation was observed to be short-term (1 to 3 months) and long-term (3 to 6 months) in northern and southern regions, respectively. In contrast, the response time of NDVI values of croplands to PET displayed a complex spatial heterogeneity. Most of the cropland vegetation and the areas with the highest potential crop yields were located in the eastern part of China; these areas also require higher levels of irrigation, which benefits the potential crop yields. This study can provide a better understanding of the agricultural ecosystems and formulate strategies for food security. [ABSTRACT FROM AUTHOR]

Global climate change is a serious threat to food and energy security. Crop growth modelling is an important tool for simulating crop food production and assisting in decision making. Planting date is one of the important model parameters. Larger-scale spatial distribution with high accuracy for planting dates is essential for the widespread application of crop growth models. In this study, a planting date prediction method based on environmental similarity was developed in accordance with the third law of geography. Spring maize planting date observations from 124 agricultural meteorological experiment stations in China over the years 1992–2010 were used as the data source. Samples spanning from 1992 to 2009 were allocated as training data, while samples from 2010 constituted the independent validation set. The results indicated that the root mean square error (RMSE) for spring maize planting date based on environmental similarity was 10 days, which is better than that of multiple regression analysis (RMSE = 13 days) in 2010. Additionally, when applied at varying scales, the accuracy of national-scale prediction was better than that of regional-scale prediction in areas with large differences in planting dates. Consequently, the method based on environmental similarity can effectively and accurately estimate planting date parameters at multiple scales and provide reasonable parameter support for large-scale crop growth modelling. [ABSTRACT FROM AUTHOR]

Suitable sowing dates are crucial in plant production to cope with climate change and ensure high-quality crop production. We hypothesize that the analysis of the effect of sowing date and climatic resources on maize kernel nutritional quality (KNQ) (crude fiber, starch, crude fat, and crude protein) might contribute to selecting appropriate sowing dates according to different production requirements and meteorological conditions. The study was based on five main local varieties in three experimental stations (early-maturing variety: Zengyu1317, Hongshuo298, Keyu15; medium-maturing variety: Xianyu335; late-maturing variety: Danyu405) in Northeast China from 2018 to 2021. The results showed that: (1) the average starch content (67.7%) and crude protein content (9.1%) of early-maturing variety maize and the crude fiber content (3.3%) and crude fat content (3.6%) of late-maturing variety maize were the highest in Northeast China; (2) the sowing date had no significant effect on the starch content, but significantly affected the crude protein and crude fiber contents, the kernel protein content of early-maturing variety maize was the highest when the sowing date was delayed for 5 days (9.8%), and the crude fiber content of medium-maturing and late-maturing variety maize (4.3% and 5.39%, respectively) was the highest when the sowing date was advanced by 10 days; (3) during the reproductive growth stage, the more light and heat resources, the less starch content and crude protein content and the more crude fat content; when the diurnal temperature range increased by 1 °C, the crude fat content decreased by 0.28%, and the crude protein content increased by 0.77%; for every 100 mm more precipitation, crude fiber and crude protein content decreased by 0.68% and 0.73%, respectively, and fat content increased by 0.15%. Our results provide a meaningful reference for maize production to cope with climate change and improve kernel quality. [ABSTRACT FROM AUTHOR]

It is of great importance to study the changes in reference evapotranspiration (ET0) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET0 data calculated using the Penman–Monteith method from 37 meteorological stations located within Guangdong Province in the humid zone of southern China from 1960 to 2020 were analyzed. The trend analysis and Mann–Kendall test were used to analyze the time series changes in ET0 and major climatic factors (air temperature (T), relative humidity (RH), sunshine duration (SD), and wind speed (u2)) for over 61 years. Sensitivity and contribution analyses were used to evaluate the driving factors of ET0. The main findings of the study are as follows: (1) the trend in average annual ET0 time series in Guangdong slightly increased at a trend rate of 1.61 mm/10a over the past 61 years, with most stations experiencing an increase in ET0. During the same period, air temperature significantly increased, while RH and SD decreased; u2 also decreased. (2) Sensitivity analysis showed that ET0 was more sensitive to RH and T than SD and u2, with ET0 being most sensitive to RH in spring and winter and T in summer and autumn. (3) The contribution analysis showed that T was the dominant factor for ET0 variation in Guangdong, followed by SD. SD was found to be the dominant factor in ET0 changes in areas where the "evaporation paradox" occurred, as well as in spring and summer. The study concludes that the climate in Guangdong became warmer and drier over the past 61 years, and if the current global warming trend continues, it will lead to higher evapotranspiration and drought occurrence in the future. [ABSTRACT FROM AUTHOR]

The responses of grassland net primary productivity (NPP) to climate change (CC) and human activities (HA) have received much attention and are inconsistent on different spatial scales. The accurate and quantitative evaluation of the impacts of CC and HA on grassland NPP at a county scale is very important to reveal the external driving factors on grassland NPP and guide the protection of the grassland ecosystem in the arid sandy area of China. In this study, the improved CASA model was adopted to quantify the grassland NPP in Otog Banner, China from 2001 to 2020. The spatiotemporal dynamics of grassland NPP and the relationships between grassland NPP and climate factors in space were analyzed using the methods of simple linear regression and relative sensitivity coefficient. Furthermore, the relative contributions to grassland NPP dynamics caused by CC and HA were explored using the quantitative method based on partial derivative. The results revealed that the mean value of grassland NPP was 175.17 g C m−2 yr−1, and exhibited a significant decrease trend periodically at a rate of 2.14 g C m−2 yr−1 from 2001 to 2020. The spatial distribution of grassland NPP increased from west to east gradually and ranged in 17.48–498.09 g C m−2 yr−1. Grassland NPP exhibited significant linear patterns along the gradients of climate factors, and was the most sensitive to sunshine duration (SSD). Approximately 86.83% of the grassland showed a degradation trend and 39.71% showed a serious degradation trend. The CC contribution to grassland NPP dynamics was 0.593 g C m−2 yr−1, and precipitation was the key driving climate factor, while the contribution of HA was −2.733 g C m−2 yr−1, which was the primary factor leading to large-scale degradation of grassland in Otog banner. This study indicates that the status of the grassland ecosystem in Otog Banner is not optimistic, and measures for grassland ecosystem restoration and improvement need to be further strengthened. [ABSTRACT FROM AUTHOR]

The increased frequency of climate extremes associated with ongoing climate change has the potential for significant impacts on maize grain yield in maize-producing regions worldwide. In this study, we used a modeling approach to investigate the effects of different types of climatic extremes on maize grain yield in Northeast China. We combined annual mean air temperature and accumulated precipitation data and divided the climate years into 9 categories, using the 10th and 90th percentiles as extreme thresholds. The climate data were represented by 1 normal climate type, 4 individual climate extremes, and 4 combined climate extremes. Changes in the frequencies of climate extremes and their impacts on maize grain yields were analyzed for two 30-year periods (period I: 1960–1989; period II: 1990–2019) using the Agricultural Production Systems sIMulator (APSIM-Maize). Compared with period I, the occurrences of the normal climate and all 3 cold-related climate extremes (i.e., cold-normal, cold-humid, and cold-dry) decreased during period II, while occurrences of the other climate extremes increased. Moreover, according to the APSIM-Maize model, the estimated yield in the years with a normal climate decreased by 4.01%; the 3 cold-related climate extremes increased yields by 26.56%, 12.10%, and 6.68%, respectively; the 2 warm-related climate extremes (warm-normal and warm-dry) and normal-humid years decreased estimated yields by 6.39%, 24.12%, and 5.10%, respectively. The increase in the occurrence of warm-humid years increased the estimated yield by 11.69%. This work confirms the adverse effects of warmer temperatures in the absence of excess rainfall on grain yield and highlights the importance of extremely dry or wet conditions under normal temperature conditions. [ABSTRACT FROM AUTHOR]

Over-fertilization has a significant impact on soil microbial properties and its ecological environment. However, the effects of long-term fertilization on microbial properties on a large scale are still vague. This meta-analysis collected 6211 data points from 109 long-term experimental sites in China to evaluate the effects of fertilizer type and fertilization duration, as well as soil and climate conditions, on the effect sizes on various microbial properties and indices. The organic fertilizers combined with straw (NPKS) and manure (NPKM) had the highest effect sizes, while the chemical fertilizers N (sole N fertilizer) and NPK (NPK fertilizer) had the lowest. When compared with the control, NPKM treatment had the highest effect size, while N treatment had the lowest effect size on MBN (111% vs. 19%), PLFA (110% vs. −7%), fungi (88% vs. 43%), Actinomycetes (97% vs. 44%), urease (77% vs. 25%), catalase (15% vs. −11%), and phosphatase (58% vs. 4%). NPKM treatment had the highest while NPK treatment had the lowest effect size on bacteria (123% vs. 33%). NPKS treatment had the highest while N treatment had the lowest effect sizes on MBC (77% vs. 8%) and invertase (59% vs. 0.2%). NPKS treatment had the highest while NPK treatment had the lowest effect size on the Shannon index (5% vs. 1%). The effect sizes of NPKM treatment were the highest predominantly in arid regions because of the naturally low organic carbon in soils of these regions. The effect sizes on various microbial properties were also highly dependent on soil texture. In coarse-textured soils the effect sizes on MBC and MBN peaked sooner compared with those of clayey or silty soils, although various enzymes were most active in silty soils during the first 10 years of fertilization. Effect sizes on microbial properties were generally higher under NPKM and NPKS treatments than under NPK or N treatments, with considerable effects due to climate conditions. The optimal field fertilizer regime could be determined based on the effects of fertilizer type on soil microorganisms under various climate conditions and soil textures. This will contribute to the microbial biodiversity and soil health of agricultural land. Such controls should be used for adaptation of fertilization strategies to global changes. [ABSTRACT FROM AUTHOR]

The oriental armyworm Mythimna separata (Walker) is a worldwide migratory pest that threatens food security in China. Previous studies have clarified the general migration regularity of M. separata in East Asia, but knowledge of migration routes over northeast China, especially in autumn as well as the impact by climate change in recent years, is still limited. From 2017 to 2020, we monitored the migration of M. separata in northeast China by searchlight traps and simulated moth trajectories by the HYSPLIT model. The M. separata moths had three main migration periods in northeast China, and there were obvious seasonal differences at different latitudes. The spring and summer migrants (late May to early-mid June and late July to early August) came from the southern Shandong Province and migrated to the north via Hebei/Shandong-Liaoning-Jilin-Heilongjiang. Moreover, more than half of the autumn trapped insects from late August to mid-late September migrated in the provinces where the sites are located, southward via Heilongjiang-Jilin-Liaoning. These results clarified the migration route of M. separata in northeast China and their relationship with the insect source in north China, thereby providing a theoretical basis for regional monitoring, early warning, and management of the pest. [ABSTRACT FROM AUTHOR]

The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and identify the potential impacts of climate change on the mean and variance of rice yields by type, keeping other factors constant. Based on the estimated production functions, the contribution rate of climatic factors to rice yield was then assessed by conducting the growth accounting of yields over the past 30 years. The results showed that both the mean rice yield and the yield variability were influenced by changes in the mean climate conditions and climatic variance. In the future, the impacts of climate change on rice yields will depend on local regions' present climatic conditions. The results have implications for improving the adaptation capacity of rice production. [ABSTRACT FROM AUTHOR]

Cosmopolitan agricultural herbivorous pests are provided with a wide range of potential hosts. Therefore, they have high carrying capacity, and can cause extremely severe damage in agroecosystems. Understanding the ecological mechanisms of their population dynamics, especially as they relate to large-scale meteorological variations and geographical landscape influences, can help us to reveal how they became such important pests. The oriental fruit moth, Grapholita molesta, is a typical example of a significant pest distributed on a large scale, which is capable of damaging fruit trees of economic value such as peach, apple, pear, etc. This pest not only occurs in China, but exists on all continents except Antarctica. In order to prevent major pests and diseases, a system of plant protection has been established gradually in peach orchards within the Modern Agro-industry Technology Research System in China (CARS) since 2009. In the system, we collected the monitoring data of G. molesta by using pheromone traps at 17 experimental stations, and then used the corresponding climate data (temperature and precipitation) to explore the link between climate factors using mixed models. The results show that both monthly mean temperature and precipitation had a significant positive correlation with the occurrence of G. molesta. Therefore, global warming with higher levels of precipitation may favor G. molesta, allowing it to outperform other potential pests at the population level in peach orchards, on a large scale. [ABSTRACT FROM AUTHOR]

Food security depends not only on the extent of climate change but also on the compensatory potentials of agronomic improvements. However, the separate contribution of these agronomic factors to rice yield remains largely unknown. Here we distinguished the impacts and relative contributions on rice yield based on statistical models and machine learning by using an observation database collected from 52 agro-meteorological stations in China from 1981 to 2018. Agronomic improvements are responsible for more than 40% of the observed rice yield change, ranging from 42.9% to 96.5% in different cropping types, and the effect increased with the latitude. Among the management considered, sowing date adjustment contributes most to late and early rice yield. Response of rice yield to nighttime temperature was stronger than that to daytime temperature, and wind speed is the main climatic contributing factor to early rice yield. The effects of wind speed on rice yield should be considered for the adaptation measures. This observation-based evidence may help guide agricultural priorities in mitigating the impact of climate change on rice yield. [ABSTRACT FROM AUTHOR]

The North China Plain is a major grain-producing area, but faces water scarcity, which directly threatens food security. The problem is more severe under climate change and the seasonal impact of climate change on winter wheat is different. Thus, it is of great importance to explore the spatiotemporal characteristics of irrigation requirements (IR) and the factors influencing IR in different growth periods of winter wheat, but it has not received much attention. Therefore, we used relative contribution, partial correlation and path analyses to assess the spatiotemporal characteristics of the IR and primary factors influencing the IR of winter wheat in various growing stages in the North China Plain. The results indicated that wind speed and net solar radiation showed a significant downward trend; no prominent trend was noted in IR (multiyear average, 302.3 mm). Throughout the growing season of winter wheat, IR increased gradually from the southern to northern extent of the North China Plain. The irrigation demand of winter wheat in stage P2 (green-up to heading) was the largest. Furthermore, the dominant drivers of IR in terms of spatial distribution and inter-annual variation were phenological period (Phe), effective precipitation (Pe) and relative humidity (RH); however, the degree of their effects varied across the growth stages and growing regions of winter wheat. Each factor exerted both direct and indirect effects on IR and Phe exhibited the strongest indirect effect on IR. The major factors contributing most to IR were Pe and RH in the P1 stage (sowing to green-up) and Phe, Pe and RH in the P2 and P3 (heading to maturity) stages. Pe and RH limited IR, whereas Phe promoted it. Our findings will help improve agricultural water management in the future. [ABSTRACT FROM AUTHOR]

Understanding the effect of climate warming and technological progress on crop production systems is crucial for developing climate adaptation strategies. This study presents a methodological framework with which to assess the suitability of the double rice cropping system in Southern China and the effects of crop management and climate warming on its distribution. The results indicate that the isolated effects of climate warming have led to the northward and westward expansions of double rice northern limits over the past six decades and an increase in suitable areas by 4.76 Mha. Under the isolated effect of crop management, the northern limits of the medium- and late-maturity double rice changed significantly due to the increased accumulated temperature required caused by varietal replacement and planting date change, which moved an average of 123 and 134 km southward, respectively. A combined scenario analysis indicated that crop management could offset the effects of climate warming and push the northern limits southward, reducing the overall suitable area by 1.31 Mha. Varietal replacement and other crop management methods should also be appropriately considered in addition to climate warming to develop locally adapted agricultural management strategies. [ABSTRACT FROM AUTHOR]

Cultivar and sowing date selection are major factors in determining the yield potential of any crop and in any region. To explore how climate change affects these choices, this study performed a regional scale analysis using the well-validated APSIM-maize model for the Northeast China Plain (NEC) which is the leading maize (Zea mays L.) producing area in China. Results indicated that high temperature had a significantly negative effect on grain yield, while effective accumulated temperature and solar radiation had significant positive effects on grain yield and kernel number. Cloudy and rainy weather in flowering stage had significant negative effects on kernel number. Delayed sowing led to less cloudy and rainy weather during flowering and reduced the negative effect on kernel number. Higher diurnal thermal range and less precipitation during the grain-filling stage also increased the 1000-kernel weight. Delayed sowing, however, also significantly increased the risk of early senescence and frost (>80%) in middle and high latitude areas. In the middle and high latitude areas of the NEC, the grain yield of a long-season cultivar (LS) under early sowing (I) (6.2–19.9%) was significantly higher than under medium sowing (II) or late sowing (III), and higher than that of an early sown (I) short-season (SS) and medium-season cultivar (MS). In the low latitude area of the NEC, the grain yield of MS under medium sowing date (II) was higher than that under I and III, meanwhile, this was also higher than that of SS and LS. Therefore, under climate warming, LS sown earlier in high and medium latitudes and MS sown medium in low latitude were the appropriate cultivar and sowing date choices, which could mitigate the stress of high temperatures and reduce the risk of early senescence and frost. Cultivar and sowing date selection are effective measures to alleviate negative effects of climate change on maize production in the NEC, and provides valuable advice for breeders on cultivar selection, and the choice of varieties and sowing dates for farmers in actual production. [ABSTRACT FROM AUTHOR]

The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production. In this study, four cultivars which were planted over more than 15 years in eight test stations in the Northern Winter Wheat Region of China were selected to investigate the relationships between growth periods, grain yields, yield components and temperatures. It was found that average temperatures and heat degree-days (HDD) during the winter wheat growing seasons tended to increase over time series at most study sites. The length of growth period and growing degree days (GDD) were not fixed for a given cultivar among different years and locations, and the variation on the periods from sowing to jointing was relatively greater than in the other periods. The increasing temperature mainly shortened the periods from sowing to jointing and jointing to anthesis, which led to the decrease in entire growth periods. Positive relationships between spike number, grain number per spike, grain yields and average temperatures were identified in the Northern Winter Wheat Region of China. The grain yield in the study area increased by 406.3 kg ha−1 for each 1 °C increase in average temperature. Further, although the positive relationship between grain yield and HDD was found in our study, the heat stress did not lead to the wheat yield decline in the study region. Temperature is a major determinant of wheat growth and development, the average temperature and the frequency of heat stresses are projected to increase in the future, so understanding the effect of temperature on wheat production and adopting appropriate adaptation are required for the implementation of food security policies. [ABSTRACT FROM AUTHOR]

We used the APSIM-Maize model to simulate maize potential yield (Yp) and rain-fed yield (Yw) when adaptation options of sowing date and planting density were adopted under Representative Concentration Pathway (RCP) 4.5 and 8.5 in the Guanzhong Plain of China. The results showed that Yp would decrease by 10.6–14.9% and 15.0–31.4% under RCP4.5 and RCP8.5 for summer maize, and 13.9–19.7% and 18.5–36.3% for spring maize, respectively. The Yw would decrease by 17.1–19.0% and 23.6–41.1% under RCP4.5 and RCP8.5 for summer maize, and 20.9–24.5% and 27.8–45.5% for spring maize, respectively. The loss of Yp and Yw could be reduced by 2.6–9.7% and 0–9.9%, respectively, under future climate for summer maize through countermeasures. For spring maize, the loss of Yp was mitigated by 14.0–25.0% and 2.0–21.8% for Yw. The contribution of changing sowing date and plant density on spring maize yield was more than summer maize, and the optimal adaptation options were more effective for spring maize. Additionally, the influences of changing sowing date and planting density on yields become weak as climate changes become more severe. Therefore, it is important to investigate the potential of other adaptation measures to cope with climate change in the Guanzhong Plain of China. [ABSTRACT FROM AUTHOR]

Accurate estimates of soil organic carbon (SOC) are critical for evaluating the impacts of crop and nutrient management practices on soil sustainability and global climate change. Temporal and spatial variations in topsoil (0–0.20 m) SOC were analyzed using 43,743 soil samples in China's croplands. The soil database in our study was collected from the International Plant Nutrition Institute (IPNI) China Program. The results showed an increasing trend in SOC density (SOCD) for both grain and cash crops from 1991 to 2012. The average SOCD increased by 16.8, 17.4, 11.8 and 8.7% in the north central, northwest, southeast and southwest regions, respectively, whereas average SOCD decreased by 1.3% for the northeast region between the 1991–2001 and 2002–2012 periods. For both grain and cash crops, the SOCD frequency distribution (%) increased in the ranges of 10–20, 20–30 and 30–40 Mg C ha−1 from the 1991–2001 to the 2002–2012, but decreased in the ranges of 0–10 and 50–60 Mg C ha−1. Additionally, SOCD increased in most major soil types across China's cropland regions, except in phaeozems, chernozems and umbrisols, where it decreased by 8.6–18.7% mainly due to water runoff, soil erosion, and low C input. The overall SOC stock (SOCS) in China's cropland increased by 260 Tg C (23.7 Tg C yr−1) from 1991–2001 to 2002–2012, which was partially due to the increased crop residue return, improved fertilization and adopted conservation tillage over the period. This SOC increase represents a potential offset in carbon dioxide (CO2) emissions that could help reduce the overall net CO2 emissions in China. [ABSTRACT FROM AUTHOR]

Climate changes show asymmetrical warming, and warming is typically greater at night than during the day. To understand how nocturnal warming (NW) affects the performance of maize (Zea mays L.), an open-field experiment with a free air temperature increase (FATI) facility was conducted for three seasons during 2014 to 2016 at Luancheng eco-agro-experimental station on the North China Plain (NCP). Three nocturnal warming scenarios were set up: the entire growing period (T1, from V4 to maturity), only the vegetative stages (T2, from V4 to a week presilking) and the reproductive stages (T3, from a week presilking to R6). The treatment without NW was the control. Maize lodged seriously in 2015 due to heavy rainfall combined with strong winds, and the experiment failed. The results from 2014 and 2016 were analyzed in this study. During the experimental duration, the average nocturnal temperature was increased by approximately 3.6 and 3.3 °C at 150 cm height and 2.0 and 1.7 °C at the soil surface during the vegetative stages. The corresponding increases were 2.1 and 2.5 °C and 0.7 and 1.2 °C at the soil surface during the reproductive stages in 2014 and 2016, respectively, as compared with that of the CK treatment. NW during the whole growth period significantly decreased maize yield for the two seasons. Treatment T2 had a smaller impact on maize yield than T1 and T3. The silking stage was delayed by 2 days in 2014 and 2016 under T1. As a result, presilking duration and VT-R1 interval were prolonged by 1–2 days; and the postsilking duration were shortened by 1–3 days under T1. The soil moisture in the warmed plots was slightly lower than that in the control plots in the 2014 and during the stages before the earlier grain-filling stages in 2016, but NW decreased soil water content greatly at the later grain-filling stages in 2016, which caused the fast green leaf senescence and exacerbated the negative effects of NW on maize yield. NW for the whole growth duration (T1) significantly decreased seed weight and harvest index. NW increased leaf nighttime respiration rate in both seasons. No significant effects of NW on ear leaf net photosynthesis, leaf area, and specific leaf weight at early grain-filling stage were observed, irrespective of the warming stage and season. The results suggested that reproductive stages were more sensitive to NW compared to vegetative stages under the growing conditions of NCP. The negative effects of NW were worsened in dry seasons. The reduction in maize yield with nocturnal warming was driven by the reduction in the aboveground carbon allocation from shoot to grain during postanthesis stage. [ABSTRACT FROM AUTHOR]

In this study, the crop environment resource synthesis maize (CERES-Maize) model was used to explore the effects of declining sunshine hours (SSH), decreasing daily maximum temperature (Tmax), and cultivar replacements on growth processes and yields of maize in Northern China, a principal region of maize production. SSH were found to decrease at 189 of 246 meteorological stations in the northern provinces of China over the period of 1994–2012, and a decrease in Tmax was also seen at many of these stations. The most significant decrease in these two climate variables occurred during June to September, a period for summer maize growth. For this study, seven crop field stations in the ShaanXi province, in the Guanzhong Plain, were selected, all of which showed a downward trend in SSH and Tmax over the period of 1994–2012. The CERES-Maize model was first calibrated and validated against yield observations for these stations over the same period, and the yield simulations matched very well with observations. The model was then driven by the detrended SSH and Tmax data, and the simulations were compared with those with a trend in these two input variables. The decline in SSH was found to reduce the maize yield by 8% on average over these stations due mostly to limited root growth, and the decline for shorter SSH reduced the yield more than that for longer SSH. Meanwhile, the decrease in higher Tmax increased the yield by extending the growth period, while the decrease in lower Tmax reduced the yield by lowering the thermal time. In addition, the observed yield showed a significant upward trend, and our modeling results indicate that this increase can be attributed mainly to the frequent cultivar replacements over our study period. The replaced cultivars usually had a longer growth period than the prior ones, which compensated for the yield loss due to fewer SSH. Net maize production decreased with the combined effects of the declines in SSH and Tmax on yields. This study quantifies the contribution of changes in climate and cultivars to maize growth processes and yields and provides strong insights into maize production under a complex dynamic climate system. [ABSTRACT FROM AUTHOR]

The threat of accelerating climate change on species distribution now and in the future is a topic of increasing research interest. However, little work has been undertaken to assess how shifting climates will affect the suitability of tea cultivation. Therefore, we used MaxEnt modelling to project the impact of current and future climatic scenarios on the potential distribution of tea across the four tea-producing countries of China, India, Kenya and Sri Lanka. Projections were made for the years 2050 and 2070 with three Representative Concentration Pathways (RCPs) using seven bioclimatic predictors under three global circulation models (GCMs). The current and future habitat suitability for tea predicted by the models produced a high accuracy rate, with high areas under the receiver operating characteristic curve (AUCs) for all tested RCPs under the three GCMs for the four countries. The mean true skill statistic (TSS) values for tea in Sri Lanka, Kenya, India and China were 0.80, 0.91, 0.91, and 0.74, respectively. The kappa values (k) of the current and future models for all four countries ranged from 0.40 to 0.75, which indicates that the overall performance of the model was good. The precipitation seasonality and annual precipitation were found to be the most influential variables in Sri Lanka and India, respectively, while annual mean temperature was the most effective contributor for determining the suitability of habitat for tea in Kenya and China. An important proviso is that some existing tea-growing areas will face reduced suitability for future tea cultivation suggesting that by 2050 there will be a drastic reduction in the optimal suitability by averages of 26.2%, 14%, and 4.7% in Kenya, Sri Lanka and China, respectively. The optimal suitability will be reduced by 15.1%, 28.6% and 2.6% in Kenya, Sri Lanka and China, respectively, by 2070. India displays an advantage in projected future climates as it gains optimal suitability areas of 15% by 2050 and 25% by 2070. [ABSTRACT FROM AUTHOR]