Spatiotemporal variability of rain-on-snow events in the arid region of Northwest China

Rain-on-snow(ROS)events involve rainfall on snow surfaces,and the occurrence of ROS events can exacerbate water scarcity and ecosystem vulnerability in the arid region of Northwest China(ARNC).In this study,using daily snow depth data and daily meteorological data from 68 meteorological stations provided by the China Meteorological Administration National Meteorological Information Centre,we investigated the spatiotemporal variability of ROS events in the ARNC from 1978 to 2015 and examined the factors affecting these events and possible changes of future ROS events in the ARNC.The results showed that ROS events in the ARNC mainly occurred from October to May of the following year and were largely distributed in the Qilian Mountains,Tianshan Mountains,Ili River Valley,Tacheng Prefecture,and Altay Prefecture,with the Ili River Valley,Tacheng City,and Altay Mountains exhibiting the most occurrences.Based on the intensity of ROS events,the areas with the highest risk of flooding resulting from ROS events in the ARNC were the Tianshan Mountains,Ili River Valley,Tacheng City,and Altay Mountains.The number and intensity of ROS events in the ARNC largely increased from 1978 to 2015,mainly influenced by air temperature and the number of rainfall days.However,due to the snowpack abundance in areas experiencing frequent ROS events in the ARNC,snowpack changes exerted slight impact on ROS events,which is a temporary phenomenon.Furthermore,elevation imposed lesser impact on ROS events in the ARNC than other factors.In the ARNC,the start time of rainfall and the end time of snowpack gradually advanced from the spring of the current year to the winter of the previous year,while the end time of rainfall and the start time of snowpack gradually delayed from autumn to winter.This may lead to more ROS events in winter in the future.These results could provide a sound basis for managing water resources and mitigating related disasters caused by ROS events in the ARNC.

Spatio-temporal variation of depth to groundwater level and its driving factors in arid and semi-arid regions of India

Climate change and increasing anthropogenic activities,such as over-exploitation of groundwater,are exerting unavoidable stress on groundwater resources.This study investigated the spatio-temporal variation of depth to groundwater level(DGWL)and the impacts of climatic(precipitation,maximum temperature,and minimum temperature)and anthropogenic(gross district product(GDP),population,and net irrigated area(NIA))variables on DGWL during 1994-2020.The study considered DGWL in 113 observation wells and piezometers located in arid western plains(Barmer and Jodhpur districts)and semi-arid eastern plains(Jaipur,Ajmer,Dausa,and Tonk districts)of Rajasthan State,India.Statistical methods were employed to examine the annual and seasonal patterns of DGWL,and the generalized additive model(GAM)was used to determine the impacts of climatic and anthropogenic variables on DGWL.During 1994-2020,except for Barmer District,where the mean annual DGWL was almost constant(around 26.50 m),all other districts exhibited increase in DGWL,with Ajmer District experiencing the most increase.The results also revealed that 36 observation wells and piezometers showed a statistically significant annual increasing trend in DGWL and 34 observation wells and piezometers exhibited a statistically significant decreasing trend in DGWL.Similarly,32 observation wells and piezometers showed an statistically significant increasing trend and 37 observation wells and piezometers showed a statistically significant decreasing trend in winter;33 observation wells and piezometers indicated a statistically significant increasing trend and 34 had a statistically significant decreasing trend in post-monsoon;35 observation wells and piezometers exhibited a statistically significant increasing trend and 32 observation wells and piezometers showed a statistically significant decreasing trend in pre-monsoon;and 36 observation wells and piezometers reflected a statistically significant increasing trend and 30 observation wells and piezometers reflected a statistically significant decreasing trend in monsoon.Interestingly,most of the observation wells and piezometers with increasing trends of DGWL were located in Dausa and Jaipur districts.Furthermore,the GAM analysis revealed that climatic variables,such as precipitation,significantly affected DGWL in Barmer District,and DGWL in all other districts was influenced by anthropogenic variables,including GDP,NIA,and population.As a result,stringent regulations should be implemented to curb excessive groundwater extraction,manage agricultural water demand,initiate proactive aquifer recharge programs,and strengthen sustainable management in these water-scarce regions.

Innovative Technologies for Large-Scale Water Production in Arid Regions: Strategies for Sustainable Development

Water scarcity in arid regions poses significant challenges to sustainable development and human well-being. This article explores both existing and innovative technologies and methods to produce large amounts of water to address these challenges effectively. Key approaches include atmospheric water generation, advanced desalination techniques, innovative water collection methods such as fog nets and dew harvesting, geothermal water extraction, and water recycling and reuse. Each method is evaluated for its feasibility with existing technology, potential time of implementation, required investments, and specific challenges. By leveraging these technologies and combining them into a multifaceted water management strategy, it is possible to enhance water security, support agricultural and industrial activities, and improve living conditions in arid regions. Collaborative efforts between governments, private sector entities, and research institutions are crucial to advancing these technologies and ensuring their sustainable implementation. The article provides a comprehensive overview of the current state of these technologies, their potential for large-scale application, and recommendations for future research and development.

Estimating the Drought-Induced Yield Loss for Winter Wheat in a Semi-Arid Region of the Southern United States Using a Drought Index

The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.

Study on Soil Microbiotic Crust and Its Influences on Sand-fixing Vegetation in Arid Desert Region

Based on secular fixed_site data in the artificial sand_fixing vegetation district at the southeast fringe of the Tengger Desert, the formative characteristics of soil microbiotic crusts and its influences on vegetation dynamics were analyzed. Once sand barrier and artificial vegetation have stabilized the surface of the sifting sand, could form aeolian deposition crust and then evolve into algae_dominated crust. Such processes result from the interactions of physical effects of atmospheric dust and silt deposition on sand surface, sinking and raindrop impact, and soil microorganism activities. Under the condition of less than 200 mm precipitation, the presence of microbiotic crust changes the soil hydraulic conductivity, alters the temporal and spatial distribution of the limited precipitation in sand layer and leads to the decline of deep_rooted shrubs. The development of microbiotic crust and subsurface soil affects the plant growth and seed rain distribution, as a result, the diversity of plant species gradually tend to become saturated and finally affects the vegetation stability.

Pollen Assemblage Features of Modern Water Samples from the Shiyang River Drainage, Arid Region of China

Pollen analysis of 30 modem water samples from the Shivang River, an internal river system located between the Tengger and Badain Jaran deserts, Northwest China was carried out to examine the river's capacity to carry pollen and spores, and to assess the contribution of the water-borne pollen to pollen assemblages in lake sediments at the end of the river system. Results indicate the pollen assemblages in water samples consist of both local and upland pollen. Percentages of upland pollen reach 30% - 60%, and pollen assemblages in water samples do not indicate the nature of local vegetation at the sampling sites. Fluvial currents have the capacity to transport large quantities of pollen long distances, and the contribution of this fluvial transported pollen is relatively high, For example, percentages of Picea Dietr. pollen in water samples at sampling sites 130 km and 145 km away from Picea forests reach 16.5% and 7.7%, respectively. Fluvial pollen transport occurs primarily during flood periods, and pollen concentrations from the flood samples are 17.1 - 12.5 times those from normal fluvial flow. Reservoirs affect pollen transportation since pollen is deposited at reservoir inlets and pollen concentrations are much reduced at reservoir outlets. Human activity can thus change natural features of pollen transportation and deposition. The main factors influencing pollen concentrations and assemblages are sampling time, sampling location, and rainfall intensity.

Interactions between Vegetation and Climatic Factors in Typical Arid and Humid Regions of China Based on NDVI

According to the distribution of arid and humid regions in China,the typical arid region (Erjina),the typical semi-arid/semi-humid region (Guanzhong basin/Loess Plateau) and the typical humid region (Poyang Lake basin) were selected as the study areas.Based on NDVI data from 1982 to 2000 and meteorological observing data of three study areas from 1981 to 2000,the interactions between vegetation NDVI and climatic factors (temperature and precipitation) in typical arid and humid regions were discussed in this study.The results showed that in the responses of vegetation to climatic factors,vegetation in the typical arid region (Erjina) was more sensitive to precipitation,while vegetation in the typical semi-arid/semi-humid region (Guanzhong basin/Loess Plateau) was more sensitive to both temperature and precipitation,and vegetation in the typical humid region (Poyang Lake basin) was more sensitive to temperature.As for effects of vegetation on climatic factors,there was a remarkable negative correlation between vegetation NDVI in the past winter and temperature in the present summer,and also a significant positive correlation between vegetation NDVI in the past winter and precipitation in the present summer.However,in the typical semi-arid/semi-humid region (Guanzhong basin/Loess Plateau),there was a significant positive correlation between vegetation NDVI in the present spring and temperature in the present summer.

Effects of Enhanced Ultraviolet Radiation-B on Maize in Arid Regions of Middle-high Elevation

[Objective] The experiment aimed to explore the influence of enhanced ultraviolet radiation-B on maize in arid regions of middle-high elevation for correct assessing the influence of enhanced ultraviolet radiation-B on maize and providing scientific reference to make proper countermeasures. [ Method] The location test in field and lift lamp of UV-B were used to observe the changes of maize height, leaf area and number of green leaves under influences of different UV-B radiation. [ Result] In arid regions of middle-high elevation, enhanced ultraviolet radiation-B could dwarf maize plant, decrease leaf area, decline number of green leaves and yield. The reason of decreasing leaf area was that enhanced ultraviolet radiation-B shortened leaf length and leaf width while the reason of declining yield was that yield components were all negatively influ- enced and with the increase of ultraviolet radiation-B, the yield declined dramatically. [ Concluslonl The result of this experiment would be good for maize production in arid regions of middle-high elevation.

Changes in Mean and Extreme Temperature and Precipitation over the Arid Region of Northwestern China： Observation and Projection

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally, the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21 st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing.

Runoff Responses to Climate Change in Arid Region of Northwestern China During 1960-2010

Based on runoff, air temperature, and precipitation data from 1960 to 2010, the effects of climate change on water resources in the arid region of the northwestern China were investigated. The long-term trends of hydroclimatic variables were studied by using both Mann-Kendall test and distributed-free cumulative sum （CUSUM） chart test. Results indicate that the mean annual air temperature increases significantly from 1960 to 2010. The annual precipitation exhibits an increasing trend, especially in the south slope of the Tianshan Mountains and the North Uygur Autonomous Region of Xinjiang in the study period. Step changes occur in 1988 in the mean annual air temperature time series and in 1991 in the precipitation time series. The runoff in different basins shows different trends, i.e., significantly increasing in the Kaidu River, the Aksu River and the Shule River, and decreasing in the Shiyang River. Correlation analy- sis reveals that the runoff in the North Xinjiang （i.e., the Weigan River, the Heihe River, and the Shiyang River） has a strong positive relationship with rainfall, while that in the south slope of the Tianshan Mountains, the middle section of the north slope of the Tianshan Mountains and the Shule River has a strong positive relationship with air temperature. The trends of rtmoff have strong negative correla- tions with glacier coverage and the proportion of glacier water in runoff. From the late 1980s, the climate has become warm and wet in the arid region of the northwestern China. The change in runoff is interacted with air temperature, precipitation and glacier coverage. The results show that streamflow in the arid region of the northwestern China is sensitive to climate change, which can be used as a reference for regional water resource assessment and management.

Study on Soil Salinization Information in Arid Region Using Remote Sensing Technique

Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus （ETM＋） image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data. Principal component analysis （PCA） is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help the classification precision of a decision tree to be improved. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. According to the research, the third principal component （PC3） is an effective variable in the decision tree classification for salinized soil information extraction. The research demonstrated that the PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM＋ sensor （TM1） was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk （Tamarix chinensis Lour）; and areas comprising mixed water bodies and vegetation can be identified using the spectral indices MNDWI （modified normalized difference water index） and NDVI （normalized difference vegetation index）. Based upon this analysis, a decision tree classifier was applied to classify landcover types with different levels of soil saline. The results were checked using a statistical accuracy assessment. The overall accuracy of the classification was 94.80%, which suggested that the decision tree model is a simple and effective method with relatively high precision.

Effects of cotton field management practices on soil CO2 emission and C balance in an arid region of Northwest China

Changes in both soil organic C storage and soil respiration in farmland ecosystems may affect atmospheric CO2 concentration and global C cycle. The objective of this field experiment was to study the effects of three crop field management practices on soil CO2 emission and C balance in a cotton field in an arid region of Northwest China. The three management practices were irrigation methods（drip and flood）, stubble managements（stubble-incorporated and stubble-removed） and fertilizer amendments（no fertilizer（CK）, chicken manure（OM）, inorganic N, P and K fertilizer（NPK）, and inorganic fertilizer plus chicken manure（NPK＋OM））. The results showed that within the C pool range, soil CO2 emission during the whole growing season was higher in the drip irrigation treatment than in the corresponding flood irrigation treatment, while soil organic C concentration was larger in the flood irrigation treatment than in the corresponding drip irrigation treatment. Furthermore, soil CO2 emission and organic C concentration were all higher in the stubble-incorporated treatment than in the corresponding stubble-removed treatment, and larger in the NPK＋OM treatment than in the other three fertilizer amendments within the C pool range. The combination of flood irrigation, stubble incorporation and application of either NPK＋OM or OM increased soil organic C concentration in the 0-60 cm soil depth. Calculation of net ecosystem productivity（NEP） under different management practices indicated that the combination of drip irrigation, stubble incorporation and NPK＋OM increased the size of the C pool most, followed by the combination of drip irrigation, stubble incorporation and NPK. In conclusion, management practices have significant impacts on soil CO2 emission, organic C concentration and C balance in cotton fields. Consequently, appropriate management practices, such as the combination of drip irrigation, stubble incorporation, and either NPK＋OM or NPK could increase soil C storage in cotton fields of Northwest China.

Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region

Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.

Hydrological and water cycle processes of inland river basins in the arid region of Northwest China

The increasing shortage in water resources is a key factor affecting sustainable socio-economic development in the arid region of Northwest China(ARNC). Water shortages also affect the stability of the region's oasis ecosystem. This paper summarizes the hydrological processes and water cycle of inland river basins in the ARNC, focusing on the following aspects: the spatial-temporal features of water resources(including air water vapor resources, runoff, and glacial meltwater) and their driving forces; the characteristics of streamflow composition in the inland river basins; the characteristics and main controlling factors of baseflow in the inland rivers; and anticipated future changes in hydrological processes and water resources. The results indicate that:(1) although the runoff in most inland rivers in the ARNC showed a significant increasing trend, both the glaciated area and glacial ice reserves have been reduced in the mountains;(2) snow melt and glacier melt are extremely important hydrological processes in the ARNC, especially in the Kunlun and Tianshan mountains;(3) baseflow in the inland rivers of the ARNC is the result of climate change and human activities, with the main driving factors being the reduction in forest area and the over-exploitation and utilization of groundwater in the river basins; and(4) the contradictions among water resources, ecology and economy will further increase in the future. The findings of this study might also help strengthen the ecological, economic and social sustainable development in the study region.

miR-340-5p靶向调控ARID1A对甲状腺癌活性、迁移和侵袭的影响

目的 探讨miR-340-5p靶向调控富含AT的相互作用结构域(ARID)1A对甲状腺癌活性、迁移和侵袭的影响。方法 通过实时荧光定-聚合酶链反应(RT-qPCR)和Western印迹检测miR-340-5p和ARID1A在甲状腺癌细胞中表达水平。通过噻唑蓝(MTT)和Transwell实验检测转染miR-340-5p抑制物后癌细胞活性、迁移和侵袭变化。双荧光素酶报告基因检测miR-340-5p和ARID1A的靶向结合关系。最后通过同时敲低miR-340-5p和ARID1A的回复实验验证miR-340-5p调控ARID1A影响癌症发展。结果 miR-340-5p在甲状腺癌细胞中明显高表达,ARID1A表达明显较低(P<0.05)。通过抑制BCPAP细胞中miR-340-5p表达明显减少了癌细胞活性、迁移和侵袭水平。miR-340-5p和ARID1A具有直接靶向结合关系。敲降ARID1A能够明显逆转miR-340-5p抑制物对BCPAP细胞活性、迁移和侵袭的抑制作用。结论 miR-340-5p是甲状腺癌中的促癌基因,ARID1A为miR-340-5p的靶标下游,miR-340-5p通过靶向调控ARID1A促进甲状腺癌细胞活性、迁移和侵袭。

Can climate change influence agricultural GTFP in arid and semi-arid regions of Northwest China?

There are eight provinces and autonomous regions(Gansu Province,Ningxia Hui Autonomous Region,Xinjiang Uygur Autonomous Region,Inner Mongolia Autonomous Region,Tibet Autonomous Region,Qinghai Province,Shanxi Province,and Shaanxi Province)in Northwest China,most areas of which are located in arid and semi-arid regions(northwest of the 400 mm precipitation line),accounting for 58.74%of the country's land area and sustaining approximately 7.84×10^6 people.Because of drought conditions and fragile ecology,these regions cannot develop agriculture at the expense of the environment.Given the challenges of global warming,the green total factor productivity(GTFP),taking CO2 emissions as an undesirable output,is an effective index for measuring the sustainability of agricultural development.Agricultural GTFP can be influenced by both internal production factors(labor force,machinery,land,agricultural plastic film,diesel,pesticide,and fertilizer)and external climate factors(temperature,precipitation,and sunshine duration).In this study,we used the Super-slacks-based measure(Super-SBM)model to measure agricultural GTFP during the period 2000-2016 at the regional level.Our results show that the average agricultural GTFP of most provinces and autonomous regions in arid and semi-arid regions underwent a fluctuating increase during the study period(2000-2016),and the fluctuation was caused by the production factors(input and output factors).To improve agricultural GTFP,Shaanxi,Shanxi,and Gansu should reduce agricultural labor force input;Shaanxi,Inner Mongolia,Gansu,and Shanxi should decrease machinery input;Shaanxi,Inner Mongolia,Xinjiang,and Shanxi should reduce fertilizer input;Shaanxi,Xinjiang,Gansu,and Ningxia should reduce diesel input;Xinjiang and Gansu should decrease plastic film input;and Gansu,Shanxi,and Inner Mongolia should cut pesticide input.Desirable output agricultural earnings should be increased in Qinghai and Tibet,and undesirable output(CO2 emissions)should be reduced in Inner Mongolia,Xinjiang,Gansu,and Shaanxi.Agricultural GTFP is influenced not only by internal production factors but also by external climate factors.To determine the influence of climate factors on GTFP in these provinces and autonomous regions,we used a Geographical Detector(Geodetector)model to analyze the influence of climate factors(temperature,precipitation,and sunshine duration)and identify the relationships between different climate factors and GTFP.We found that temperature played a significant role in the spatial heterogeneity of GTFP among provinces and autonomous regions in arid and semi-arid regions.For Xinjiang,Inner Mongolia,and Tibet,a suitable average annual temperature would be in the range of 7℃-9℃;for Gansu,Shanxi,and Ningxia,it would be 11℃-13℃;and for Shaanxi,it would be 15℃-17℃.Stable climatic conditions and more efficient production are prerequisites for the development of sustainable agriculture.Hence,in the agricultural production process,reducing the redundancy of input factors is the best way to reduce CO2 emissions and to maintain temperatures,thereby improving the agricultural GTFP.The significance of this study is that it explores the impact of both internal production factors and external climatic factors on the development of sustainable agriculture in arid and semi-arid regions,identifying an effective way forward for the arid and semi-arid regions of Northwest China.

Influence of groundwater level change on vegetation coverage and their spatial variation in arid regions

Sampling and testing are conducted on groundwater depth and vegetation coverage in the 670 km2 of the Sangong River Basin and semi-variance function analysis is made afterwards on the data obtained by the application of geo-statistics. Results showed that the variance curve of the groundwater depth and vegetation coverage displays an exponential model. Analysis of sampling data in 2003 indicates that the groundwater depth and vegetation coverage change similarly in space in this area. The Sangong River Basin is composed of upper oasis, middle ecotone and lower sand dune. In oasis and ecotone, influenced by irrigation of the adjoining oasis, groundwater level has been raised and soil water content also increased compared with sand dune nearby, vegetation developed well. But in the lower reaches of the Sangong River Basin, because of descending of groundwater level, soil water content decreased and vegetation degenerated. From oasis to abandoned land and desert grassland, vegetation coverage and groundwater level changed greatly with significant difference respectively in spatial variation. Distinct but similar spatial variability exists among the groundwater depth and vegetation coverage in the study area, namely, the vegetation coverage decreasing (increasing) as the groundwater depth increases (decreases). This illustrates the great dependence of vegetation coverage on groundwater depth in arid regions and further implies that among the great number of factors affecting vegetation coverage in arid regions, groundwater depth turns out to be the most determinant one.

Impacts of Climate Change on Net Primary Productivity in Arid and Semiarid Regions of China

In recent years, with the constant change in the global climate, the effect of climate factors on net primary productivity(NPP) has become a hot research topic. However, two opposing views have been presented in this research area: global NPP increases with global warming, and global NPP decreases with global warming. The main reasons for these two opposite results are the tremendous differences among seasonal and annual climate variables, and the growth of plants in accordance with these climate variables. Therefore, it will fail to fully clarify the relation between vegetation growth and climate changes by research that relies solely on annual data. With seasonal climate variables, we may clarify the relation between vegetation growth and climate changes more accurately. Our research examined the arid and semiarid areas in China(ASAC), which account for one quarter of the total area of China. The ecological environment of these areas is fragile and easily affected by human activities. We analyzed the influence of climate changes, especially the changes in seasonal climate variables, on NPP, with Climatic Research Unit(CRU) climatic data and Moderate Resolution Imaging Spectroradiometer(MODIS) satellite remote data, for the years 2000–2010. The results indicate that: for annual climatic data, the percentage of the ASAC in which NPP is positively correlated with temperature is 66.11%, and 91.47% of the ASAC demonstrates a positive correlation between NPP and precipitation. Precipitation is more positively correlated with NPP than temperature in the ASAC. For seasonal climatic data, the correlation between NPP and spring temperature shows significant regional differences. Positive correlation areas are concentrated in the eastern portion of the ASAC, while the western section of the ASAC generally shows a negative correlation. However, in summer, most areas in the ASAC show a negative correlation between NPP and temperature. In autumn, precipitation is less important in the west, as opposed to the east, in which it is critically important. Temperatures in winter are a limiting factor for NPP throughout the region. The findings of this research not only underline the importance of seasonal climate variables for vegetation growth, but also suggest that the effects of seasonal climate variables on NPP should be explored further in related research in the future.

Effects of uniconazole with or without micronutrient on the lignin biosynthesis,lodging resistance,and winter wheat production in semiarid regions

Lodging stress results in grain yield and quality reduction in wheat. Uniconazole, a potential plant growth regulator significantly enhances lignin biosynthesis and thus provides mechanical strength to plants in order to cope with lodging stress. A field study was conducted during the 2015–2016 and 2016–2017 growing seasons, to investigate the effects of uniconazole sole application or with micronutrient on the lignin biosynthesis, lodging resistance, and production of winter wheat. In the first experiment, uniconazole at concentrations of 0(CK), 15(US1), 30(US2), and 45(US3) mg L^-1 was applied as sole seed soaking, while in the second experiment with manganese(Mn) at concentration of 0.06 g L^-1 Mn, 0.06 g L^-1 Mn+ 15 mg L^-1 uniconazole(UMS1), 0.06 g L^-1 Mn+30 mg L^-1 uniconazole(UMS2), and 0.06 g L^-1 Mn+45 mg L^-1 uniconazole(UMS3), respectively. Uniconazole sole application or with micronutrient significantly increased the lignin content by improving the lignin-related enzyme activities of phenylalanine ammonia-lyase, cinnamyl alcohol dehydrogenase, tyrosine ammonialyase, and peroxidase, ameliorating basal internode characteristics, and breaking strength. The spike length, spike diameter, spikes/plant, weight/spike, yield/spike, and grain yield increased and then decreased with uniconazole application at a higher concentration, where their maximum values were recorded with UMS2 and US2 treatments. The lignin accumulation was positively correlated with lignin-related enzyme activities and breaking strength while, negatively correlated with lodging rate. Uniconazole significantly improved the lignin biosynthesis, lodging resistance, and grain yield of winter wheat and the treatments which showed the greatest effects were uniconazole seed soaking with micronutrient at a concentration of 30 mg L^-1 and 0.06 g L^-1 , and uniconazole sole seed soaking at a concentration of 30 mg L^-1 .

Numerical Study of Impacts of Soil Moisture on the Diurnal and Seasonal Cycles of Sensible/Latent Heat Fluxes over Semi-arid Region

The semi-arid regions, as climatic and ecosystem transitional zones, are the most vulnerable to global environmental change. Earlier researches indicate that the semi-arid regions are characterized by strong landatmosphere coupling in which soil moisture is the crucial variable in land surface processes. In this paper, we investigate the sensitivity of the sensible/latent heat fluxes to soil moisture during the growing season based on the enhanced observations at Tongyu in the Jilin province of China, a reference site of international Coordinated Energy and Water Cycle Observations Project （CEOP） in the semi-arid regions, by using a sophisticated land surface model （NCAR_CLM3.0）. Comparisons between the observed and simulated sensible/latent heat fluxes indicate that the soil moisture has obvious effects on the sensible/latent heat fluxes in terms of diurnal cycle and seasonal evolution. Better representation of the soil moisture could improve the model performance to a large degree. Therefore, for the purpose of simulating the land-atmosphere interaction and predicting the climate and water resource changes in semi-arid regions, it is necessary to enhance the description of the soil moisture distribution both in the way of observation and its treatment in land surface models.