Northwestern China Research Articles

Spatio-Temporal Evolution, Internal Diversity, and Driving Factors of Economy of Guanzhong Plain Urban Agglomeration in Northwestern China Based on Nighttime Light Data

Urban agglomeration (UA) is a highly developed spatial form of urban complex, which is one of the important carriers of regional economic cooperation, international industrial division of labor, and flow of capital and information elements. In China, urban agglomerations (UAs) have become the spatial subject of the national new-type urbanization strategy since the early 21st century and have made irreplaceable contributions to China’s urbanization and economic development. The Guanzhong Plain urban agglomeration (GPUA) is an important economic growth pole in northwest China and a key node in China’s open-door pattern. Exploring the spatial and temporal characteristics and driving factors of its economic development will be an important revelation for the promotion of high-quality economic development of the GPUA. This paper characterizes the level of economic development of GPUA with a long series of nighttime light data between 2002 and 2022. The standard deviation ellipse, spatial autocorrelation analysis, the economic difference index, and grey correlation analysis are used to analyze the characteristics of spatio-temporal evolution, internal diversity, and driving factors of economic development of the GPUA. The results show that the economic development level of the GPUA continued to increase from 2002 to 2022. The spatial distribution of the GPUA economy is “northeast-southwest” axial distribution, and the center of gravity of economic development gradually moves westward. The differences in the level of economic development within the GPUA show a typical core–periphery structure, but the degree of difference tends to weaken over time. The internal expansion force and economic promotion force were the dominant factors for the economic development of the GPUA in the early years. However, with the passage of time, scientific and technological support and government support have gradually become the main influencing factors for the economic development of the GPUA nowadays.

Identification of Priority Supply Areas for Carbon Sinks Based on Ecosystem Service Flow: A Case Study for the Hexi Region in Northwestern China

The development and implementation of regional protection plans for ecosystem carbon storage services have been recognized as crucial actions for mitigating global climate change. However, the supply areas of carbon sequestration in terms of ecosystem service flows in inland regions are still less evaluated. The goal of this study is to identify the priority-ranked supply areas for carbon sinks. Here, we conducted a case study in the Hexi Region of northwestern China and proposed a framework to quantify the priority supply areas for carbon sinks from the perspective of ecosystem service flows. Firstly, we quantified the carbon service supply and demand areas by combining carbon models (i.e., the Carnegie–Ames–Stanford Approach model and soil respiration models) with socioeconomic and natural factors. Then, we introduced a breaking point formula to estimate ecosystem service flow, specifically focusing on distance or range. Finally, we determined priority supply areas for carbon sinks based on the Zonation model. The results showed that significantly higher carbon sequestration values were detected in the Qilian Mountains, ranging from 2.0 to 3.0 t hm−2, in comparison with desert oasis areas, where the supply values ranged from 0 to 0.01 t hm−2. The urban areas and rural settlements within the study area are characterized by higher values of carbon emissions compared to those in the Qilian Mountains and deserts. The carbon flow analysis demonstrated that the middle and northern parts of the study area, being characterized by lower precipitation and sandy landscapes, were identified as locations with low carbon sequestration fluxes (<1.0 t hm−2). In addition, the mountainous regions were identified as the main highest priority area for ecosystem carbon sequestration, covering 8.33% of total area of the Hexi Region. Our findings highlighted the importance of the Qilian Mountains in terms of sustaining carbon sequestration service supply in the Hexi Region and targeted ecological protection practices to be implemented going forward.

Prediction of Summer Precipitation via Machine Learning with Key Climate Variables：A Case Study in Xinjiang, China

Study region: Xinjiang is located in the mid-latitude region of Eurasia in northwestern China. Precipitation is predominantly concentrated in northern Xinjiang, while southern Xinjiang remains comparatively arid. Summer precipitation accounts for 54.4% of the annual total. Study focus: This study aims to develop a machine learning model to predict summer precipitation (June–August) in XJ and explore the key variables contributing to summer precipitation in this region. The SHapley Additive exPlanations method was integrated with an extreme tree model to quantify the contributions of variables towards precipitation. Artificial neural networks, support vector machines, and extreme gradient boosting were considered to predict summer precipitation. To train the ML model, we used precipitation data from 1961 to 2012, whilst the forecast results from 2013 to 2017 were used for validation.New hydrological insights for the regions: The results demonstrated that the ANN model achieved robust performance during both the training and validation periods. For Northern and Southern XJ, the Mean Absolute Error and Root Mean Square Error of the ANN model were 15.34 (20.40) and 23.21 (30.01), respectively. The SHAP analysis showed that in the context of Northern Xinjiang, the Niño B Sea Surface Temperature Anomaly, Western Pacific Subtropical High Intensity, Pacific Subtropical High Intensity, and Multivariate ENSO Index play crucial roles in the prediction of summer precipitation. In Southern Xinjiang, the South China Sea Subtropical High Intensity, South China Sea Subtropical High Area, Western Pacific Warm Pool Strength, and Atlantic multidecadal oscillation have emerged as key variables affecting summer precipitation forecasting.

Early Neolithic plant exploitation in north-western China: archaeobotanical evidence from Beiliu

China was a centre for early plant domestication, millets in the north and rice in the south, with both crops then spreading widely. The Laoguantai Culture (c. 8000–7000 BP) of the middle Yellow River region encompasses a crucial stage in the transition from hunting and gathering to farming, yet its subsistence basis is poorly understood. The authors present archaeobotanical data from the site of Beiliu indicating that farmers exploited a variety of wild and cultivated plants. The predominance of broomcorn millet accords with other Neolithic cultures in northern China but the presence of rice—some of the earliest directly dated examples—opens questions about the integration of rice cultivation into local subsistence strategies.

The olfactory recognition between leaf-cutter bee Megachile saussurei and alfalfa floral volatiles mediated by odorant binding protein 4 (MsauOBP4).

Megachile saussurei (Hymenoptera, Megachilidae) is a primary insect pollinator of alfalfa (Medicago sativa L.) in northwestern China. However, the mechanisms underlying the olfactory responses of M. saussurei induced by alfalfa volatiles is still unclear. Here, the interaction between MsauOBP4 and alfalfa floral volatiles was first elucidated. Results suggested that thirty-two alfalfa floral volatiles were identified and MsauOBP4 was successfully expressed with the consistent molecular mass as predicted results. MsauOBP4 displayed a broad binding spectrum to 32 volatiles, among which MsauOBP4 showed the strongest binding ability to (Z)-3-Hexen-1-ol. In the Y-tube olfactometer behavioral bioassay, M. saussurei elicited the most significant behavioral preference (Z)-3-Hexen-1-ol. MsauOBP4 showed an optimal binding feature to (Z)-3-Hexen-1-ol and valine was the key residue in binding the ligands. After silencing the MsauOBP4, the preference and EAG values of M. saussurei to (Z)-3-Hexen-1-ol were significantly decreased and selection rate of M. saussurei to alfalfa flowers dropped to 57.50 % from 83.33 %. These findings indicated that (Z)-3-Hexen-1-ol is a crucial component in the host location process mediated by MsauOBP4.

Film mulching can alleviate soil quality decrease and produce high maize yield under different irrigation strategies

Plastic film mulching (PM) combined with irrigation is widely adopted to improve crop yields, water and nitrogen efficiency, especially in arid farming areas. Despite its benefits, the effects of this method on soil quality and its subsequent impact on crop productivity and resource efficiency have not been thoroughly investigated. In this study, we formulated a soil quality indicator (SQI) from five years of field experiments in the Hetao Irrigation District (HID) of Northwestern China. The treatments included border irrigation as the control treatment (CK), CK combined with PM (BI_PM), and three water level drip irrigation treatments combined with PM. Three threshold values of soil matric potential for drip irrigation were −10 kPa (HDI_PM), −30 kPa (MDI_PM), and −50 kPa (LDI_PM). We then examined the SQI changes based on measured multiple soil properties and assessed their implications for maize yield, irrigation water productivity (IWP), and partial factor productivity of nitrogen (PFPN). We found: (1) from 2016 to 2020, HDI_PM achieved the highest average yield (15.77 t ha–1), IWP (3.73 kg m–3), and PFPN (63.18 kg kg–1), showing increases of 54.77 %, 84.90 %, and 96.93 % over the control treatment, respectively; (2) no significant variations in the SQI were observed for HDI_PM in 2020 in the topsoil (0–30 cm) and subsoil (30–60 cm) compared to the initial condition. However, CK, BI_PM, MDI_PM, and LDI_PM showed reductions in SQI in both soil layers, primarily due to decreased soil organic carbon (SOC) and structural stability, along with increased sand content and soil salinity; (3) according to the linear mixed-effects model, a low SQI (< 0.43), elevated temperatures, and drought indices negatively impact yield. Hence, we advocate for HDI_PM to maximize yield and PFPN. To enhance soil quality, identifying agronomic practices that increase SOC and reduce soil salinity in the HID is crucial.

Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study.

Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions. This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas. A total of 10,520 participants aged 18-85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the International Diabetes Federation (IDF) criteria. Eight anthropometric indexes were examined, including BMI, waist-to-height ratio (WHtR), weight-adjusted waist index (WWI), conicity index, a body shape index (ABSI), lipid accumulation products (LAP), visceral obesity index (VAI), and the triglyceride-glucose (TyG) index. Logistic regression analysis and restricted cubic splines (RCSs) were applied to identify the association between the anthropometric indexes. The receiver operating characteristic curve and the area under the curve (AUC) were analyzed to identify and compare the discriminative power of anthropometric indexes in identifying MetS. The Youden index was used to determine a range of optimal diagnostic thresholds. Logistic regression analysis was applied to identify the association between the anthropometric indexes. A total of 3324 (31.60%) participants were diagnosed with MetS. After adjusting for age, ethnicity, current residence, education level, habitual alcohol consumption, and tobacco use, all the 8 indexes were positively correlated with the risks of MetS (P<.05). LAP presented the highest adjusted odds ratios (adjOR 35.69, 95% CI 34.59-36.80), followed by WHtR (adjOR 29.27, 95% CI 28.00-30.55), conicity index (adjOR 11.58, 95% CI 10.95-12.22), TyG index (adjOR 5.53, 95% CI 5.07-6.04), BMI (adjOR 3.88, 95% CI 3.71-4.05), WWI (adjOR 3.23, 95% CI 3.02-3.46), VAI (adjOR 2.11, 95% CI 2.02-2.20), and ABSI (adjOR 1.71, 95% CI 1.62-1.80). Significantly nonlinear associations between the 8 indexes and the risk of MetS (all Pnonlinear<.001) were observed in the RCSs. WHtR was the strongest predictor of MetS for males (AUC 0.91, 95% CI 0.90-0.92; optimal cutoff 0.53). LAP were the strongest predictor of MetS for females (AUC 0.89, 95% CI 0.89-0.90; optimal cutoff 28.67). Statistical differences were present between WHtR and all other 7 anthropometric indexes among males and overall (all P<.05). In females, the AUC values between LAP and BMI, WWI, ABSI, conicity index, VAI, and TyG index were significantly different (P<.001). No statistical difference was observed between LAP and WHtR among females. According to 8 anthropometric and lipid-related indices, it is suggested that WHtR and LAP are the most appropriate indexes for identifying the presence of MetS in resource-limited areas.

Long-term distribution and evolution trends of absorption aerosol optical depth with different chemical components in global and typical regions

Different types of atmospheric aerosols have different climatic effects. In this study, MERRA-2 reanalysis data of absorption aerosol optical depth (AAOD) products at 550 nm from 1980 to 2018 were used to analyse the long-term distribution characteristics and evolution trends of the AAOD of different chemical components globally and in 12 typical study areas. We also analysed the seasonal and interannual monthly variations of the different chemical components of AAOD. In the 40-year study period from 1980 to 2018, the maximum value of total AAOD (TAAOD) appears in the southern regions of SD (Sahara Desert), CSA (Central Southern Africa), NC (Northern China), SC (Southern China), and SEA (Southeastern Asia) (> 0.040). The highest value of dust AAOD (DUAAOD) is in SD (0.030–0.040), and the contribution rate reaches 80 %; while in SC, SEA, and AMZ, black carbon AAOD (BCAAOD) contributes 80 %–90 %. The high-value area of DUAAOD in SD-ME-NWC expands in spring, and the dust belt formed in summer results in a larger DUAAOD (> 0.050). The proportion of BCAAOD in autumn and winter is larger in the dust belt, which is another major contributor to AAOD in this region. The monthly distributions of TAAOD in SEA, CSA, NC, and AMZ are mainly affected by biomass combustion, while the DU in ME (Middle East), NWC (Northwestern China), and SD has a greater effect on AAOD, and the TAAOD in NEA (Northeastern Asia), WEU (Western Europe), EUS (Eastern United States), SC, SA (Southern Asia), and other regions is mainly affected by both DU and BC + OC (in which OC refers to organic carbon). The interannual variations of BCAAOD and OCAAOD tend to be flat before 2000, and then show an increasing trend. BCAAOD has the largest relative contribution (at about 60 %), followed by DUAAOD (at about 30 %), and then OCAAOD has the smallest contribution (at less than 10 %). From a global perspective, AAOD shows different increasing trends during 1980–2018, 1980–1992, and 1993–2005, and decreases or even completely reverses during 2006–2018. This paper provides the distribution characteristics and evolutionary trends of different chemical components of AAOD, which can improve scientific understanding of global- and regional-scale aerosols and their climatic effects.

Cryptoporus qinlingensis sp. nov., the third species of Cryptoporus (Polyporaceae, Polyporales) from northwestern China

The macrofungal genus Cryptoporus consists of only two species presently. Another species of the genus was collected from Qinling Mountains in northwestern China, and here described as a novel species based on morphological and phylogenetic evidence. In morphology, the novel species C. qinlingensis sp. nov. can be distinguished from related species by its relatively larger fruiting bodies (projecting up to 5.5 cm, 6.5 cm wide and 2.5 cm thick at base) with distinct odor of medicinal herbs when fresh, cream to reddish brown pileal surface, thick context (up to 1.5 cm thick), slim cystidioles (2.5–5.5 μm wide), host (pythogenesis on trunk of Pinus massoniana Lamb.) and sequence data. Phylogenetic analyses based on both ITS and multi-locus sequences (nLSU, tef1, mtSSU, rpb2 and nSSU) were carried out. Both morphological and molecular analyses confirm the distinct taxonomic status of C. qinlingensis.

Human settlement and destructive activities disrupt the positive contribution of dust to plant biomass growth over the past 2000 years

The dual pressures of global warming and increased anthropogenic activities pose significant threats to terrestrial vegetation ecosystems. To better understand the impacts of climate change and human activities on terrestrial vegetation ecosystems, we reconstructed the changes in vegetation and plant biomass over the past 4500 years using n-alkane records from sediments of two alpine lakes in northwestern China: Xiannv Lake and Tianchi Lake. Our results indicate that changes in the spatial variability of plant biomass are not related to temperature and precipitation. Furthermore, CO2 fertilization and nutrient inputs from dust contributed to the observed changes in plant biomass. We also compared the history of human activities in the Tianshan Mountains, the eastern Silk Road, and the Hunsandak Sandy Land, and find that the demand for plant resources—whether for human settlement, military construction, or warfare—may have caused a sudden decline in terrestrial vegetation, thereby disrupting the positive effects of dust on plant biomass growth.

Study on the Interactions Between Urbanization, Tourism, and the Ecological Environment in Underdeveloped Regions: PVAR Model Analysis Based on Data from 32 Chinese Cities

Clarifying the dynamic relationships between urbanization, tourism development, and the ecological environment in underdeveloped regions can assist local governments in optimizing industrial upgrades and environmental management through effective policy planning, despite resource constraints, thereby promoting high-quality urban development. This study, based on data from 32 cities in northwestern China, constructs a multi-dimensional evaluation system incorporating demographic, economic, social, and environmental indicators. Using a PVAR model, the long-term dynamic interactions between urbanization, tourism, and the ecological environment are explored. The results indicate that, although in the initial stages, the three subsystems can support each other, in the long term, tourism has a positive impact on urbanization and the ecological environment, whereas both urbanization and the ecological environment negatively impact tourism. The interaction effects between urbanization, tourism, and the ecological environment are weak, with contribution rates below 20%, failing to create a synergistic development. The primary reason for this issue is that urbanization development policies lag behind the needs of tourism and ecological environment development. Policy recommendations are provided, including optimizing cross-sector collaboration strategies, enhancing urbanization quality, and prioritizing environmental protection, to foster coordinated development among the three.

Radiocarbon chronology and settlement patterns in the Bronze Age of the Qaidam Basin, Northwestern China

Prehistoric settlement patterns on the Tibetan Plateau, particularly in the Qaidam Basin, have drawn significant scholarly interest. Yet, limited data have hindered a comprehensive understanding the Bronze Age chronology and landscape exploitation in this region. This paper presents 24 newly obtained radiocarbon dates from eight archaeological sites within the Qaidam Basin on the Tibetan Plateau. Integrated with existing 14 C data and spatial analysis, these findings reveal an overall continuous occupation of the basin from ca. 3600–2500 calBP, with a gradual shift from expansive lowland settlements to smaller, ephemeral high-altitude structures, identified around 3350 calBP. This change is consistent with demonstrated periods of climate degradation which likely drove strategic adaptations in landscape management and subsistence methods. Overall, this research not only establishes a more robust chronology for the Qaidam Basin’s Bronze Age, but also advances the discussion on human-environment interactions in high-altitude areas during late prehistory.

Maize yield is associated with abscisic acid and water potential under reduced soil water supply but with indoleacetic acid in genotypic renewal

Irrigation and breeding are important practices for improving yield and water use efficiency of maize (Zea mays L.) in arid regions. However, the physiological mechanisms of yield under varying water supplies and genotypes remain unclear. Here, we examine the different physiological mechanisms underlying maize yield responses to varying soil water supplies and three genotypes (MC670, ZD958, and ZD2#) cultivated in northwestern China over the past five decades. The declining water supply significantly reduced maize leaf hydraulic transport, stomatal conductance (gs), net photosynthetic rate (A), yield, kernel number, biomass, and evapotranspiration (ET). Conversely, it led to an increase in abscisic acid (ABA), hydrogen peroxide, intrinsic water use efficiency, and water productivity. Interestingly, there was no significant impact on indoleacetic acid (IAA), thousand kernel weight, or harvest index (HI). Breeding efforts increased leaf IAA levels, biomass, thousand kernel weight, yield, HI, and water productivity without altering physiological traits or ET. The superior yield of MC670 could be attributed to a simultaneous enhancement in both kernel number and thousand kernel weight, while ZD958 exhibited greater yield stability. ABA and hydraulic traits (predawn leaf water potential, leaf water potential, and whole-plant hydraulic conductance) coordinated gs under reduced soil water supply, while ABA and predawn leaf water potential regulated yield by modulating gs to affect both A and ET. Breeding for yield gains was associated with IAA-induced enhancements in biomass and HI, independent of key physiological traits (e.g., gs and A) and ET. The observed increase in water productivity primarily stemmed from notable yield improvements rather than alterations in ET. Hence, the selection of high-yielding genotypes under water-limited and well-watered conditions requires consideration of water-related physiological traits and IAA levels, respectively.

Aggregate Size Mediated the Changes in Soil Microbial Communities After the Afforestation of a Former Dryland in Northwestern China

Although the afforestation of former arable lands is a common global land-use conversion, its impact on soil microbial communities at the aggregate scale has not been adequately addressed. In this study, soil samples were categorized into large macroaggregates (LM, &gt;2 mm), small macroaggregates (SM, 2–0.25 mm), and microaggregates (MI, &lt;0.25 mm) to assess the changes in microbial composition, diversity, network complexity, and network stability within soil aggregates after the afforestation of a former dryland in northwestern China. The results revealed that afforestation enhanced the relative abundance of Actinobacteriota, Chloroflexi, Ascomycota, and Mortierellomycota within the soil aggregates, suggesting that these phyla may have greater advantages in microbial communities post-afforestation. The Shannon–Wiener and Pielou indices for bacterial communities showed no significant differences between land-use types across all aggregate fractions. However, the alpha diversity of fungal communities within the LM and SM significantly increased after afforestation. Bray–Curtis dissimilarity indices showed that afforestation altered bacterial beta diversity within the LM and MI but had a minimal impact on fungal beta diversity across all three aggregate fractions. The topological features of cross-kingdom microbial co-occurrence networks within the soil aggregates generally exhibited a decreasing trend post-afforestation, indicating a simplification of microbial community structure. The reduced robustness of microbial networks within the LM and SM fractions implies that afforestation also destabilized the structure of microbial communities within the macroaggregates. The composition of the soil microbial communities correlated closely with soil carbon and nitrogen contents, especially within the two macroaggregate fractions. The linkages suggests that improved resource conditions could be a key driver behind the shifts in microbial communities within soil aggregates following afforestation. Our findings indicate that the impact of afforestation on soil microbial ecology can be better understood by soil aggregate fractionation.

Comprehensive evaluation of nine evapotranspiration products from remote sensing, gauge upscaling and land surface model over China.

Benefiting from the advancements in monitoring and measuring terrestrial evapotranspiration (ET), diverse ET products have been proliferated. This study evaluated nine ET products from three types, namely remote sensing-based retrievals (GLEAM, PML and PLSH), gauge-based upscaling (FCCRU, FCGSW and FCWFD) and land surface model-based reanalysis (ERA5-Land, GLDAS and MERRA) over China and its seven climate zones. Both spatial and temporal change trends in ET were investigated, and period feature were analyzed. Then, in-situ ET observations were used for validating the performances of ET products. The results demonstrate that all products show comparable performances in spatial distribution over China, but the mean ET values present evident discrepancies (433-563 mm/a). Among them, reanalysis ET products reproduce higher ET, but with less difference. In terms of climate sub-regions, the most significant discrepancies are located in QT. In addition, PLSH, MERRA and GLDAS present substantial increasing trends, while all three gauge-based upscaling ET products display decreasing trends. Regionally, all the ET products show positive trends in QT. Moreover, most of ET products present apparent periodic oscillation ranging from 2.0-5.5 year scales. At point scale, most ET products perform well at NMG and CBS sites (CC > 0.80, RMSE < 20 mm/month). However, general underestimations appear in northwestern China sites (HB and DX), and systematical overestimation exist in southern China sites (DHS and XSBN). By comparison, remote sensing-based ET products performs best, followed by gauge-based upscaling ET, comparatively, reanalysis-based ET products have poorest performances against in-situ ET observations. This study can provide valuable reference information for the selection of proper ET datasets for the hydrological simulation and analysis over China.

CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration

Abstract. Accurate maps of irrigation extent and dynamics are crucial for studying food security and its far-reaching impacts on Earth systems and the environment. While several efforts have been made to map irrigated area in China, few have provided multiyear maps, incorporated national land surveys, addressed data discrepancies, and considered the fractional coverage of cropland within coarse-resolution pixels. Here, we addressed these important gaps and developed new annual maps of China's irrigated cropland from 2000 to 2020, named CIrrMap250 (China's irrigation map with a 250 m resolution). We harmonized irrigation statistics and surveys and reconciled them with remote sensing data. The refined estimates of irrigated area were then integrated with multiple remote sensing data (i.e. vegetation indices, hybrid cropland products, and paddy field maps) and an irrigation suitability map by means of a semi-automatic training approach. We evaluated our CIrrMap250 maps using ∼ 20 000 reference samples, high-resolution irrigation water withdrawal data, and existing local to nationwide maps. Our CIrrMap250 maps demonstrated an overall accuracy of 0.79–0.88 for the years 2000, 2010, and 2020 and outperformed currently available maps. The CIrrMap250-estimated irrigation area explained 50 %–60 % of the variance in irrigation water withdrawal across China. CIrrMap250 revealed that China's irrigation area increased by about 180 000 km2 (or 25 %) from 2000 to 2020, with the majority (61 %) occurring in the water-unsustainable regions facing severe to extreme water stress. Moreover, our product unveiled a noticeable northward shift of China's irrigation area, attributed to substantial expansions in irrigated cropland across northeastern and northwestern China. The accurate representation of irrigation extent in CIrrMap250 will greatly support hydrologic, agricultural, and climate studies in China, aiding in improved water and land resources management. CIrrMap250 can be accessed at https://doi.org/10.6084/m9.figshare.24814293.v2 (Zhang et al., 2023a).

Elymusmultiramosus (Poaceae), a new species from the north-western Qinghai-Tibetan Plateau, China.

A new species from China, Elymusmultiramosus Y.C. Zhang, sp. nov. is described and illustrated herein, based on morphological characters and molecular phylogenetic analysis. The taxonomic descriptions of E.multiramosus and the comparison with related species are presented. The taxonomic distinctiveness of this new species was inferred by Maximum Likelihood (ML) analysis and Bayesian phylogenetic analysis, based on the complete chloroplast genome sequence. It is assigned to the Elymus section and bears similarity to Elymusnutans Griseb. However, it can be easily distinguished from other species by its compound spike, in contrast to the simple spike inflorescence typical of those species. The compound spike is characterised by rhachillas that are extended at the base of the main axis, giving rise to 3-6 mini-spike-like branches. Notably, these branches significantly increase in length from the top towards the bottom of the compound spike. In the molecular phylogeny, Elymusmultiramosus from Qinghai, north-western China, is phylogenetically positioned as a distinct lineage. The lineage comprising Elymussinosubmuticus from Sichuan, east of the Tibetan Plateau and Elymusnutans from the Himalayas forms a sister group to Elymusmultiramosus, suggesting that these three species share a common ancestor that is distinct from the lineage leading to Elymusatratus from Gansu, north of the Tibetan Plateau.

High-resolution assessment of wind energy potential in the Hami region of Northwestern China

Abstract Wind energy plays a pivotal role in the global effort to mitigate climate change, with China emerging as a leader in renewable energy adoption. The Hami region in northwestern China stands out as a crucial area for wind power development, given its substantial wind resources and strategic importance in China’s energy landscape. However, existing studies on wind energy potential vary widely and involve large uncertainties due to sparse measurements and coarse resolution, highlighting the need for more precise assessments to guide policy decisions and optimize energy utilization. This study leverages high-resolution ERA5 reanalysis data and advanced wind turbine technology to assess wind energy potential in the Hami region, taking into account factors including wind speed patterns, turbine heights, and geographical constraints. The comparison with in-situ data demonstrated that high-resolution ERA5 reanalyzed wind speeds enable to capture multi-year wind speed variations in this region. We find substantial potential for wind energy in Hami, with energy densities exceeding 200 W m−2 in the high-potential wind zones. Importantly, this study identifies a new high-potential area in eastern Hami, termed the East Wind Zone. Our high-resolution assessment of wind energy potential at different heights over the past two decades reveals long-term trends and seasonal variations. Increasing the hub height from 95 m to 140 m raises the average wind power generation potential across Hami by 31.3 GWh yr−1. Our findings highlight the importance of strategic wind farm placement to maximize renewable energy output and provide insights for policy and industry, supporting China’s renewable energy goals.

Effects of Irrigation Amount and Salinity Levels on Maize (Zea mays L.) Growth, Water Productivity and Carbon Emissions in Arid Region of Northwest China

To address the growing scarcity of freshwater resources, the use of saline water for agricultural irrigation is gaining increasing attention. This study presents findings from a two-year field experiment conducted during the 2023 and 2024 maize-growing seasons in northwestern China. The objective of the experiment was to evaluate the main and interactive effects of saline irrigation water on soil water–salt dynamics, maize growth, photosynthetic characteristics, water productivity, and carbon emissions. The experiment involved nine treatments with three irrigation amounts: 4500 m3 hm−2 (W1), 5625 m3 hm−2 (W2), and 6750 m3 hm−2 (W3), combined with three water salinity levels: 0.85 g L−1 (S1, freshwater), 3 g L−1 (S2), and 5 g L−1 (S3). Results indicated that both irrigation amount and salinity level significantly affected water–salt dynamics, with more soil accumulating in the 0–100 cm soil layer under saline irrigation water; however, this effect diminished with higher irrigation amounts. The maximum leaf area index and plant height were affected by both the irrigation amount and salinity level, as well as their interaction. Photosynthetic capacity declined with increasing salinity of the irrigation water, ultimately reducing grain yield and irrigation water use efficiency. Compared to freshwater (S1), the average maize grain yield under S2 and S3 treatments decreased by 6.28% and 15.43% in 2023 and by 7.82% and 17.48% in 2024, respectively. Additionally, for the same irrigation amount, higher salinity of the irrigation water (S2, S3) significantly reduced total soil CO2 emissions, with reductions of 10.08% and 27.53% in 2023, and 11.97% and 28.01% in 2024, respectively. In summary, to optimize the utilization of saline water, enhance maize yield, and improve soil carbon sequestration, we recommend maintaining the salinity of irrigation water below 3 g L−1, and using an irrigation amount of 6750 m3 hm−2 (W3S2) for optimal outcomes in the study area.

The Impact of Seasonal Climate on Dryland Vegetation NPP: The Mediating Role of Phenology

Dryland ecosystems are highly sensitive to climate change, making vegetation monitoring crucial for understanding ecological dynamics in these regions. In recent years, climate change, combined with large-scale ecological restoration efforts, has led significant greening in China’s arid areas. However, the mechanisms through which seasonal climate variations regulate vegetation growth are not yet fully understood. This study hypothesizes that seasonal climate change affects net primary productivity (NPP) of vegetation by influencing phenology. We focused on China’s Windbreak and Sand-Fixation Ecological Function Conservation Areas (WSEFCAs) as representative regions of dryland vegetation. The Carnegie–Ames–Stanford Approach (CASA) model was used to estimate vegetation NPP from 2000 to 2020. To extract phenological information, NDVI data were processed using Savitzky–Golay (S–G) filtering and threshold methods to determine the start of season (SOS) and end of season (EOS). The structural equation model (SEM) was constructed to quantitatively assess the contributions of climate change (temperature and precipitation) and phenology to variations in vegetation NPP, identifying the pathways of influence. The results indicate that the average annual NPP in WSEFCAs increased from 55.55 gC/(m2·a) to 75.01 gC/(m2·a), exhibiting uneven spatial distribution. The pathways through which seasonal climate affects vegetation NPP are more complex and uneven. Summer precipitation directly promoted NPP growth (direct effect = 0.243, p &lt; 0.001) while also indirectly enhancing NPP by significantly advancing SOS (0.433, p &lt; 0.001) and delaying EOS (−0.271, p &lt; 0.001), with an indirect effect of 0.133. This finding highlights the critical role of phenology in vegetation growth, particularly in regions with substantial seasonal climate fluctuations. Although the overall ecological environment of WSEFCAs has improved, significant regional disparities remain, especially in northwestern China. This study introduces causal mediation analysis to systematically explore the mechanisms through which seasonal climate change impacts vegetation NPP in WSEFCAs, providing new insights into the broader implications of climate change and offering scientific support for ecological restoration and management strategies in arid regions.