Assessment of rehabilitation strategies for lakes affected by anthropogenic and climatic changes: A case study of the Urmia Lake, Iran

Over the last three decades,more than half of the world's large lakes and wetlands have experienced significant shrinkage,primarily due to climate change and extensive water consumption for agriculture and other human needs.The desiccation of lakes leads to severe environmental,economic,and social repercussions.Urmia Lake,located in northwestern Iran and representing a vital natural ecosystem,has experienced a volume reduction of over 90.0%.Our research evaluated diverse water management strategies within the Urmia Lake basin and prospects of inter-basin water transfers.This study focused on strategies to safeguard the environmental water rights of the Urmia Lake by utilizing the modeling and simulating(MODSIM)model.The model simulated changes in the lake's water volume under various scenarios.These included diverting water from incoming rivers,cutting agricultural water use by 40.0%,releasing dam water in non-agricultural seasons,treated wastewater utilization,and inter-basin transfers.Analytical hierarchy process(AHP)was utilized to analyze the simulation results.Expert opinions with AHP analysis,acted as a multi-criteria decision-making tool to evaluate the simulation and determine the optimal water supply source priority for the Urmia Lake.Our findings underscore the critical importance of reducing agricultural water consumption as the foremost step in preserving the lake.Following this,inter-basin water transfers are suggested,with a detailed consideration of the inherent challenges and limitations faced by the source watersheds.It is imperative to conduct assessments on the impacts of these transfers on the downstream users and the potential environmental risks,advocating for a diplomatic and cooperative approach with adjacent country.This study also aims to forecast the volumes of water that can be transferred under different climatic conditions—drought,normal,and wet years—to inform strategic water management planning for the Urmia Lake.According to our projection,implementing the strategic scenarios outlined could significantly augment the lake's level and volume,potentially by 3.57×109–9.38×109 m3 over the coming 10 a and 3.57×109–10.70×109 m3 in the subsequent 15 a.

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District,Ghana

Smallholder farmers in Ahafo Ano North District,Ghana,face multiple climatic and non-climatic issues.This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions(FGDs)with 10 respondents.The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022.The relative importance index(RII)value was used to rank the climatic and non-climatic factors perceived by respondents.The socioeconomic characteristics affecting smallholder farmers’perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model.Results showed that mean annual rainfall decreased(P>0.05)but mean annual temperature significantly increased(P<0.05)from 2002 to 2022 in the district.The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature(RII=0.498),erratic rainfall(RII=0.485),and increased windstorms(RII=0.475).The critical non-climatic factors were high cost of farm inputs(RII=0.485),high cost of healthcare(RII=0.435),and poor condition of roads to farms(RII=0.415).Smallholder farmers’perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics(P<0.05).This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors.Therefore,to enhance the resilience of smallholder farmers to climate change,it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

Sorghum Conservation Techniques in Three Agro-Climatic Zones and Their Impact on Food Security in Burkina Faso

The objective of this study was to examine the sorghum preservation techniques in response to climate variability and to evaluate the prevalence of aflatoxin B1 in selected sorghum stocks in Burkina Faso. The cross-sectional study was conducted over a period of six months, from October 2020 to January 2021. A questionnaire was administered to 450 sorghum farmers in order to ascertain their knowledge and practices with regard to conservation techniques. A total of 23 farmers’ stocks were sampled for the determination of aflatoxin B1 using the Enzyme-Linked Immunosorbent Assay (ELISA) method and for the assessment of moisture levels using the Association of Official Agricultural Chemists (AOAC) method. A total of five distinct preservation techniques were identified. The most frequently utilized techniques were straw loft (49.2%) as a storage structure, pallets (36.69%) as the structure’s internal management, plastic bags (40.42%) as packaging material, panicles (64.3%) as a form of storage, and chemical products (15.22%) as preservatives. Three biotic constraints were identified: insect (51.18%), rodent (30.14%), and mold (15.38%). Three significant abiotic constraints were identified: humidity (44.6%), lack of hygiene (15.2%), and grain immaturity (10.2%). A comparative analysis reveals that the majority of these techniques and constraints exhibit notable differences between climatic zones, largely due to the influence of climatic variability. The aflatoxin B1 level exhibited considerable variation, ranging from 0 µg/kg to 2.07 ± 0.08 µg/kg DM. Of the analyzed stocks, 38% were found to be contaminated. Abiotic and biotic factors exert influence on sorghum stocks. Chemical agents are employed for their protection, and contamination by aflatoxin B1 is a further issue. However, the levels of contamination observed are not cause for concern.

Numerical Models and Methods of Atmospheric Parameters Originating in the Formation of the Earth’s Climatic Cycle

Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in2/s for humidity, 2.993 in2/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .

Thermospheric neutral wind studies over the equatorial region:A review

Thermospheric neutral winds(TNWs)refer to the neutral gases in the thermosphere circulating as tides,which play a crucial role in the dynamics of the thermosphere-ionosphere system(TIS).Global geospace neutral winds,particularly over the magnetic equator,have been a subject of study for several decades.However,despite the known importance of neutral winds,a comprehensive understanding and characterization of the winds is still lacking.Various ground-based and satellite missions have provided valuable information on the contribution of neutral winds to the global atmospheric dynamics.However,efforts in the global monitoring of neutral winds are still lacking,and the drivers behind the behavior of TNWs as well as their influence on the TIS remain incomplete.To address these knowledge gaps in the global circulation of TNWs,it is crucial to develop a deep understanding of the neutral wind characteristics over different regions.The low-latitude equatorial region in particular has been observed to exert complex influences on TNWs because of the unique effects of the Earth’s magnetic field at the dip equator.Studying neutral winds over this region will provide valuable insights into the unique dynamics and processes that occur in this region,thereby enhancing our understanding of their role in the overall dynamics of the TIS.Additionally,through empirical observations,an improved ability to accurately model and predict the behavior of this region can be achieved.This review article addresses challenges in understanding equatorial winds by reviewing historical measurements,current missions,and the interactions of ionospheric and thermospheric phenomena,emphasizing the need for comprehensive measurements to improve global atmospheric dynamics and weather forecasting.

Climatic drivers of the Canadian wildfire episode in 2023

2023年5月加拿大发生极端野火事件并持续4个月时间.野火污染物排放对当地和下风向的空气质量造成了严重影响.本文对驱动此次野火事件的气象因子和相关大尺度环流进行了探究.研究表明,此次极端野火排放的二氧化碳相较往年同期增长了0.37Gt (527.1%).受罗斯贝波频散影响,同期加拿大中西部区域出现持续的位势高度正异常,促进气流下沉并引发局地高温,中西部区域5-6月最高温平均上升8.11℃,部分区域甚至超过10℃,导致野火排放的显著增长.受有利地形和泛北极地区快速增暖的影响,预期未来加拿大中西部发生极端野火的概率可能会显著上升.

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for diagnosis.The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification.Most of the extracted image features are irrelevant and lead to an increase in computation time.Therefore,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features.This process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel distributions.The similarity between the pixels over the various distribution patterns with high indexes is recommended for disease diagnosis.Later,the correlation based on intensity and distribution is analyzed to improve the feature selection congruency.Therefore,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the distribution.Now,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of selection.Therefore,the probability of feature selection,regardless of the textures and medical image patterns,is improved.This process enhances the performance of ML applications for different medical image processing.The proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected dataset.The mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

Burden of mental disorders and risk factors in the Western Pacific region from 1990 to 2021

BACKGROUND The burden of mental disorders(MD)in the Western Pacific Region(WPR)re-mains a critical public health concern,with substantial variations across demogra-phics and countries.AIM To analyze the burden of MD in the WPR from 1990 to 2021,along with associated risk factors,to reveal changing trends and emerging challenges.METHODS We used data from the Global Burden of Disease 2021,analyzing prevalence,incidence,and disability-adjusted life years(DALYs)of MD from 1990 to 2021.Statistical methods included age-standardisation and uncertainty analysis to address variations in population structure and data completeness.RESULTS Between 1990 and 2021,the prevalence of MD rose from 174.40 million cases[95%uncertainty interval(UI):160.17-189.84]to 234.90 million cases(95%UI:219.04-252.50),with corresponding DALYs increasing from 22.8 million(95%UI:17.22-28.79)to 32.07 million(95%UI:24.50-40.68).During this period,the burden of MD shifted towards older age groups.Depressive and anxiety disorders were predominant,with females showing higher DALYs for depressive and anxiety disorders,and males more affected by conduct disorders,attention-deficit hyperactivity disorder,and autism spectrum disorders.Australia,New Zealand,and Malaysia reported the highest burdens,whereas Vietnam,China,and Brunei Darussalam reported the lowest.Additionally,childhood sexual abuse and bullying,and intimate partner violence emerged as significant risk factors.CONCLUSION This study highlights the significant burden of MD in the WPR,with variations by age,gender,and nation.The coronavirus disease 2019 pandemic has exacerbated the situation,emphasizing the need for a coordinated response.

Geographic patterns and ecological causes of phylogenetic structure in mosses along an elevational gradient in the central Himalaya

Understanding the underlying mechanisms driving species assembly along elevational gradients is of great interest in ecology and biogeography.The Himalaya is one of the world’s hotspots of biodiversity,and the elevational gradient of the central Himalaya in Nepal is one of the longest elevational gradients in the world.Mosses are important constituents of vegetation in the Himalaya,and knowledge of geographic patterns and ecological causes of phylogenetic structure of mosses along elevational gradients in the Himalaya is critical to understanding the assembly of plant diversity in general,and moss diversity in particular,in the Himalaya.Here,we investigate the relationships of phylogenetic structure metrics reflecting different evolutionary depths with elevation and climatic variables representing mean temperature and precipitation conditions,climate extremes,and climate seasonality for mosses distributed along an elevational gradient spanning about 5000 m in the central Himalaya,Nepal.For a given climatic variable,different metrics of phylogenetic structure show different spatial and climatic patterns,but all phylogenetic metrics standardized for species richness show that phylogenetic dispersion in moss assemblages tend to increase with increasing elevation and decreasing temperature.The standardized effect size of mean pairwise distance of moss assemblages shows a triphasic(zig-zag)pattern,which is generally consistent with the triphasic patterns previously found in angiosperms and ferns along the same elevational gradient.Our study shows that temperature-related variables and climate seasonality variables are more important drivers of phylogenetic dispersion in mosses in Nepal,compared with precipitation-related variables and climate extreme variables,respectively.

Evaluation of ERA5 reanalysis temperature data over the Qilian Mountains of China

Air temperature is an important indicator to analyze climate change in mountainous areas.ERA5 reanalysis air temperature data are important products that were widely used to analyze temperature change in mountainous areas.However,the reliability of ERA5 reanalysis air temperature over the Qilian Mountains(QLM)is unclear.In this study,we evaluated the reliability of ERA5 monthly averaged reanalysis 2 m air temperature data using the observations at 17 meteorological stations in the QLM from 1979 to 2017.The results showed that:ERA5 reanalysis monthly averaged air temperature data have a good applicability in the QLM in general(R2=0.99).ERA5 reanalysis temperature data overestimated the observed temperature in the QLM in general.Root mean square error(RMSE)increases with the increasing of elevation range,showing that the reliability of ERA5 reanalysis temperature data is worse in higher elevation than that in lower altitude.ERA5 reanalysis temperature can capture observational warming rates well.All the smallest warming rates of observational temperature and ERA5 reanalysis temperature are found in winter,with the warming rates of 0.393°C/10a and 0.360°C/10a,respectively.This study will provide a reference for the application of ERA5 reanalysis monthly averaged air temperature data at different elevation ranges in the Qilian Mountains.

Exploring the dynamics of creative tourism:A tourist-centric perspective to achieve economic sustainable development

Creative tourism is a dynamic and innovative approach to tourism,which points out the importance of people's active participation and their immersion in such experiences.In a vernacular context,it should attract people(local and tourists)attention to accomplish its main goals.Despite its rich cultural and natural assets,Kurdistan province faces several challenges that impact its tourism potential.To achieve that,the study uses quantitative approach to thoroughly analyze and evaluate the components of creative tourism in this province.The research focuses on tourists who visited the province's ten towns during the spring and summer of 2023.Data collection utilized a Likert-scale questionnaire ranging from"very good"to"very poor".The study employed a semistructured questionnaire developed through qualitative interviews alongside a researcher-made questionnaire validated by experts from the University of Kurdistan.The qualitative questionnaire achieved a high-reliability score of 93%using Cronbach's alpha coefficient.In-depth interviews and literary research were conducted to identify creative tourism components and indicators,informing the development of a quantitative questionnaire.Data analysis was performed using SPSS 20 and AMOS software to scrutinize the survey findings,providing insights into enhancing creative tourism strategies in Kurdistan province.The results reveal the varying significance of these dimensions,with the cultural dimension identified as the most crucial(factor loading:0.95),followed by the social(0.92),economic(0.88),and managerial/political dimensions(0.83).The study highlights the importance of cultural planning,community engagement,and infrastructural support in fostering creative tourism.Furthermore,it explores the impact of creative industries,such as music and arts rooted in Kurdish culture,on tourism development.Economic diversification and spatialphysical considerations are critical factors in enhancing Kurdistan's appeal as a creative tourism destination,emphasizing sustainable growth and cultural preservation.

Space weathering characteristics of lunar permanently shadowed regions soils:Evidence from experimental simulation

Permanently shadowed regions(PSRs)on the Moon are potential reservoirs for water ice,making them hot spots for future lunar exploration.The water ice in PSRs would cause distinctive changes in space weathering there,in particular reduction-oxidation processes that diff er from those in illuminated regions.To determine the characteris-tics of products formed during space weathering in PSRs,the lunar meteorite NWA 10203 with artifi cially added water was irradiated with a nanosecond laser to simulate a micro-meteorite bombardment of lunar soil containing water ice.The TEM results of the water-incorporated sample showed distinct amorphous rims that exhibited irregular thickness,poor stratifi cation,the appearance of bubbles,and a reduced number of npFe^(0).Additionally,EELS analysis showed the presence of ferric iron at the rim of the nanophase metallic iron particles(npFe^(0))in the amorphous rim with the involve-ment of water.The results suggest that water ice is another possible factor contributing to oxidation during microme-teorite bombardment on the lunar surface.In addition,it off ers a reference for a new space weathering model that incorporates water in PSRs,which could be widespread on asteroids with volatiles.

Assessing the impact of climate change on dissolved oxygen using a flow field ecosystem model that takes into account the anaerobic and aerobic environment of bottom sediments

This study examines the potential impacts o climate change on Lake Biwa,Japan’s largest freshwate lake,with a focus on temperature,wind speed,and pre cipitation variations.Leveraging data from the IPCC Sixth Assessment Report,including CCP scenarios,projecting a significant temperature rise of 3.3–5.7℃in the case o very high GHG emission power,the research investigates how these shifts may influence dissolved oxygen levels in Lake Biwa.Through a one-dimensional model incorporat ing sediment redox reactions,various scenarios where ai temperature and wind speed are changed are simulated.I is revealed that a 5℃increase in air temperature leads to decreasing 1-2 mg/L of dissolved oxygen concentrations from the surface layer to the bottom layer,while a decrease in air temperature tends to elevate 1–3 mg/L of oxygen lev els.Moreover,doubling wind speed enhances surface laye oxygen but diminishes it in deeper layers due to increased mixing.Seasonal variations in wind effects are noted with significant surface layer oxygen increases from 0.4to 0.8 mg/L during summer to autumn,increases from 0.4 to 0.8 mg/L in autumn to winter due to intensified vertica mixing.This phenomenon impacts the lake’s oxygen cycle year-round.In contrast,precipitation changes show limited impact on oxygen levels,suggesting minor influence com pared to other meteorological factors.The study suggests the necessity of comprehensive three-dimensional models that account for lake-specific and geographical factors fo accurate predictions of future water conditions.A holistic approach integrating nutrient levels,water temperature,and river inflow is deemed essential for sustainable management of Lake Biwa’s water resources,particularly in addressing precipitation variations.

Regional Storm Surge Forecast Method Based on a Neural Network and the Coupled ADCIRC-SWAN Model

Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.

Latitudinal patterns of tree b-diversity and relevant ecological processes vary across spatial extents in forests of southeastern China

Latitudinal patterns of treeβ-diversity reveal important insights into the biogeographical processes that influence forest ecosystems.Although previous studies have extensively documentedβ-diversity within relatively small spatial extents,the potential drivers ofβ-diversity along latitudinal gradients are still not well understood at larger spatial extents.In this study,we determined whether treeβ-diversity is correlated with latitude in forests of southeastern China,and if so,what ecological processes contribute to these patterns of treeβ-diversity.We specifically aimed to disentangle the relative contributions from interspecific aggregation and environmental filtering across various spatial extents.We delineated regional communities comprising multiple nearby national forest inventory(NFI)plots around random focal plots.The number of NFI plots in a regional community served as a surrogate for spatial extent.We also used a null model to simulate randomly assembled communities and quantify the deviation(β-deviation)between observed and expectedβ-diversity.We found thatβ-diversity decreased along a latitudinal gradient and that this pattern was clearer at larger spatial extents.In addition,latitudinal patterns ofβ-deviation were explained by the degree of species spatial aggregation.We also identified environmental factors that driveβ-deviation in these forests,including precipitation,seasonality,and temperature variation.At larger spatial extents,these environmental variables explained up to 84%of theβ-deviation.Our results reinforce that ecological processes are scale-dependent and collectively contribute to theβ-gradient in subtropical forests.We recommend that conservation efforts maintain diverse forests and heterogeneous environments at multiple spatial extents to mitigate the adverse effects of climate change.

Geographical Indications and Regional Public Brands of the Whole Rice Industry Chain in the Yangtze River Economic Belt

The Yangtze River Economic Belt is the main rice producing area in China.The rice industry chain is the agricultural pillar industry chain of this economic belt and it is the key to ensuring national food security and promoting comprehensive rural revitalization.This study discusses the entire rice industry chain in the Yangtze River Economic Belt from the national rice production functional zones,agricultural product quality and safety,national famous and excellent new agricultural products,national specialty agricultural products,"China s good grain and oil"products,and national advantageous characteristic industrial clusters.Then,it discusses the geographical indications of rice and its products in this economic belt from geographical indication products,geographical indication trademarks,agricultural geographical indications,geographical indication standards,geographical indication special indications,national geographical indication product protection demonstration zones,and Chinese geographical indication products protected by the European Union.In addition,it analyzes the five main problems between geographical indications and public brands,such as the limited use of geographical indication specific signs and the imperfect intellectual property protection system for geographical indications.Finally,it proposes eight strategies,including promoting the high-quality development of the entire rice industry chain,creating a geographical indication regional public brand for rice and its products,and implementing geographical indication protection projects.

Spatiotemporal variation and driving factors of vegetation net primary productivity in the Guan-zhong Plain Urban Agglomeration,China from 2001 to 2020

Studying the spatiotemporal variation and driving mechanisms of vegetation net primary productivity(NPP)in the Guanzhong Plain Urban Agglomeration(GPUA)of China is highly important for regional green and low-carbon development.This study used the Theil-Sen trend analysis,Mann-Kendall trend test,coefficient of variation,Hurst index,and machine learning method(eXtreme Gradient Boosting and SHapley Additive exPlanations(XGBoost-SHAP))to analyze the spatiotemporal variation of NPP in the GPUA from 2001 to 2020 and reveal its response to climate change and human activities.The results found that during 2001-2020,the averageNPP in the GPUA showed a significant upward trend,with an annual growth rate of 10.84 g C/(m^(2)•a).The multi-year average NPP in the GPUA was 484.83 g C/(m^(2)•a),with higher values in the southwestern Qinling Mountains and lower values in the central and northeastern cropland and built-up areas.The average coefficient of variation of NPP in the GPUA was 0.14,indicating a relatively stable state overall,but 72.72%of the study area showed weak anti-persistence,suggesting that NPP in most areas may have declined in the short term.According to XGBoost-SHAP analyses,elevation,land use type and precipitation were identified as the main driving factors of NPP.Appropriate precipitation and higher temperatures promote NPP growth,whereas extreme climates,high population density,and nighttime lighting inhibit NPP.This study has important theoretical and practical significance for achieving regional sustainable development,offers a scientific basis for formulating effective ecological protection and restoration strategies,and promotes green,coordinated,and sustainable development in the GPUA.

Impact of Climate Change on Crop-cropland Coupling Relationship:A Case Study of the Loess Plateau in China

Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural sustainability and food security.Taking the Loess Plateau(LP),China as an example,this study used a coupling coordination degree model and spatial autocorrelation analysis to portray the spatial and temporal features of crop-cropland coupling relationship from 2000 to 2020 and explored the impact law of climate change through geographically and temporally weighted regression(GTWR).The results were as follows:1)the crop-cropland coupling coordination degree of the LP showed a gradual upward trend from 2000 to 2020,forming a spatial pattern with lower values in the central region and higher values in the surrounding areas.2)There was a positive correlation in the spatial distribution of cropcropland coupling coordination degree in the LP from 2000 to 2020,and the high value-low value(H-L)and low value-low value(L-L)agglomerations continued to expand eastward,while the spatial and temporal evolution of the high value-high value(H-H)and low value-high value(L-H)agglomerations was not obvious.3)The impacts of climatic elements on crop-cropland coupling coordination degree in the LP showed strong heterogeneity in time scales.The inhibitory impacts of summer days(SU)and frost days(FD)accounted for a higher proportion,while the annual average temperature(TEM)had both promoting and inhibiting impacts.The impacts proportion and intensity of extreme heavy precipitation day(R25),continuous drought days(CDD),and annual precipitation(PRE)all experienced significant changes.4)In space,the impacts of SU and FD on the crop-cropland coupling coordination degree varied with latitude and altitude.The adaptability of the LP to R25 gradually strengthened,and the extensions of CDD and increase of PRE led to the increasing inhibition beyond the eastern region of LP,and TEM showed a promoting impact in the Fenwei Plain.As an important grainproducing area in China,the LP should actively deal with the impacts of climate change on the crop-cropland coupling relationship,vigorously safeguard food security,and promote sustainable agricultural development.

Mesozoic multi-direction collision tectonic evolution of the Ordos Basin, China: Insights from the detrital zircon and apatite (U-Th)/He analyses

The Ordos Basin(OB)in the western part of the North China Craton(NCC),was located at the jointed area of multi-plates and has recorded the Mesozoic tectonic characteristics.Its tectonic evolution in the Mesozoic is significant to understand the tectonic transformation of the northern margin of the NCC.In this work,the detrital zircon and apatite(U-Th)/He chronological system were analyzed in the northern part of the OB,and have provided new evidence for the regional tectonic evolution.The(U-Th)/He chronological data states the weighted ages of 240‒235 Ma,141 Ma with the peak distribution of 244 Ma,219 Ma,173 Ma,147‒132 Ma.The thermal evolution,geochronological data,and regional unconformities have proved four stages of regional tectonic evolution for the OB and its surroundings in the Mesozoic:(1)The Late Permian-Early Triassic;(2)the Late Triassic-Early Jurassic;(3)the Late Jurassic-Early Cretaceous;(4)the Late Cretaceous-Early Paleogene.It is indicated that the multi-directional convergence from the surrounding tectonic units has controlled the Mesozoic tectonic evolution of the OB.Four-stage tectonic evolution reflected the activation or end of different plate movements and provided new time constraints for the regional tectonic evolution of the NCC in the Mesozoic.

Spatial Patterns and Controlling Factors of Soil Organic Carbon and Total Nitrogen in the Three River Headwaters Region,China

The alpine ecosystem has great potential for carbon sequestration.Soil organic carbon(SOC)and total nitrogen(TN)are highly sensitive to climate change,and their dynamics are crucial to revealing the effect of climate change on the structure,function,and services of the ecosystem.However,the spatial distribution and controlling factors of SOC and TN across various soil layers and vegetation types within this unique ecosystem remain inadequately understood.In this study,256 soil samples in 89 sites were collected from the Three River Headwaters Region(TRHR)in China to investigate SOC and TN and to explore the primary factors affecting their distribution,including soil,vegetation,climate,and geography factors.The results show that SOC and TN contents in 0-20,20-40,40-60,and 60-80 cm soil layers are 24.40,18.03,14.04,12.40 g/kg and 2.46,1.90,1.51,1.17 g/kg,respectively;with higher concentrations observed in the southeastern region compared to the northwest of the TRHR.One-way analysis of variance reveals that SOC and TN levels are elevated in the alpine meadow and the alpine shrub relative to the alpine steppe in the 0-60 cm soil layers.The structural equation model explores that soil water content is the main controlling factor affecting the variation of SOC and TN.Moreover,the geography,climate,and vegetation factors notably indirectly affect SOC and TN through soil factors.Therefore,it can effectively improve soil water and nutrient conditions through vegetation restoration,soil improvement,and grazing management,and the change of SOC and TN can be fully understood by establishing monitoring networks to better protect soil carbon and nitrogen.