A framework approach for analyzing water transformation characteristics of typical watersheds in arid zones during irrigation periods

Detecting the unseen: Combining mist nets and acoustic monitoring to reveal bat diversity in a Mexican arid zone

Exon capture has emerged as a powerful and relatively cost-effective method for obtaining independently evolving nuclear loci, enabling robust phylogenetic inference across diverse taxonomic levels. While most exon capture studies have focused on resolving higher-level relationships, their potential for addressing species-level questions - particularly in refining and testing mtDNA-driven taxonomic hypotheses - is underexplored. In this study, we focus on a group of camaenid land snails endemic to the Australian Arid Zone. This genus, Catellotrachia, poses a challenge to conventional taxonomic approaches, because it comprises a series of morphologically similar species with supposedly highly restricted, yet primarily allopatric distributions. Using a published exon capture design that targets 500 orthologous nuclear loci to study deeper phylogenetic splits among the Camaenidae, here we assess the utility of these markers in resolving species-level relationships and even phylogeographic patterns to test current species hypotheses. In addition, we examine if often neglected intronic DNA can contribute to robustly resolving phylogenetic relationships. Our study proves that even a modest number of nuclear loci can effectively disentangle interspecific relationships and resolve species limits. However, the number of used markers and associated SNPs is relatively small limiting the ability to resolve the youngest splits confidently. We found that historical samples often contained rare genotypes, potentially misleading SNP-based phylogenetic analyses. We show that introns considerably increase the number of phylogenetically informative sites adding to the statistical support of phylogenetic inferences. Our findings highlight the applicability of exon capture to resolving fine-scale phylogenetic and taxonomic questions more generally.

ABSTRACT Coastal groundwater degradation and salinization from overexploitation and brine mismanagement represent urgent concerns in arid zones. To our knowledge, physics-informed neural networks (PINNs) have not yet been applied to real, highly stressed aquifers affected by seawater intrusion, pumping wells, and discharges from small-scale desalination units. In this study, we present an efficient and environmentally friendly PINN-based framework for simulating groundwater flow and solute transport. The method employs learning rate optimization to simultaneously adjust model parameters and loss function weights. The framework was developed using synthetic datasets generated by MODFLOW and MT3DMS for a coastal aquifer in northern Oman. Performance assessments of hydraulic head and concentration models demonstrated high accuracy across training, validation, and prediction phases. The PINN framework effectively captured complex interactions among recharge, pumping, and boundary conditions, while maintaining strong generalization to unseen data. Parallel coordinate plots and spatial distributions further validated the reliability and convergence behaviour of the model.

Abstract Land cover changes in arid zones with industrial agglomerations require a comprehensive spatiotemporal assessment of drought and soil airborne pollution. Geospatial maps were obtained for each level of the two time periods -2019-2021 and 2022-2024 based on the distribution and contextual significance of each parameter. An analysis of the identified trends in the climate change indicators (precipitations, evapotranspiration and land surface moister) allows us to speak about a meteorological type of drought complicated with large Kakhovka water reservoir disappearance in June 2023. At the same time, the advance of drought conditions was fixed in the LAI change in canopy density throughout the steppe zone of Ukraine by 2024. It was found that the progression of arid conditions has the character of horizontal zonality in the direction from south to north. The main differences in the risk of acid rain caused by industrial agglomerations are related to the spatial distribution of nitrogen dioxide in the atmosphere in the northern part of Ukrainian steppe.

This study investigates the transformation of river runoff and its sensitivity to changes in large-scale atmospheric circulation in the Zhaiyk–Caspian water management basin during the period of 1951–2023. The analysis is based on hydrometeorological observations data, the Vangengeim–Girs classification of macro-circulation patterns, and the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices. Correlation analysis, the Mann–Kendall test, Sen’s slope estimator, and the Pettitt test were applied to identify trends, structural shifts, and the spatial coherence of hydroclimatic changes. The results show that interannual variability in river runoff is characterized by a degree of spatial coherence, with correlation coefficients between annual streamflow records at most gauging stations reaching up to 0.95. It is demonstrated that the most pronounced changes in the hydrological regime occur during the cold season and are expressed in a statistically significant increase in winter runoff, while no significant long-term trend in annual runoff is observed. Structural shifts in winter runoff are predominantly associated with the late 1990s, whereas changes in the temperature regime are detected earlier and exhibit spatial coherence. The findings indicate that the contemporary transformation of river runoff is primarily driven by rising air temperatures and the associated intra-annual redistribution of flow.

Abstract Large-scale photovoltaic (PV) deployment and afforestation represent vital climate change mitigation strategies, yet the climate mitigation potential of PV deployment in regions where afforestation is constrained remains understudied. Using the Community Earth System Model (CESM2.1.3), we quantitatively assess the carbon reduction and surface temperature effects of large-scale PV deployment and afforestation across global potential afforestation areas. Our results reveal regional limitations of afforestation and demonstrate strong climate benefits from PV deployment in these constrained regions. Our results demonstrate that PV deployment in potential afforestation regions could reduce carbon emissions by 3.47 Gt C yr-1 while decreasing global surface temperatures by 0.08 °C, whereas afforestation yields a smaller carbon sink (0.075 Gt C yr-1) and induces slight global warming (+0.02 °C). In arid zones, where solar radiation is high and bare land is prevalent, PV deployment mitigate 2.24 Gt C yr-1 (114 Mha) and cools the surface by -0.26 °C, whereas afforestation induces warming of +0.16 °C due to albedo reduction. In boreal regions, PV deployment cools surfaces by -0.26 °C, whereas afforestation leads to a +0.21 °C warming. These results demonstrate that in regions where afforestation is limited by water scarcity or induces biophysical warming, PV deployment can provide effective climate mitigation through stable carbon reduction and surface cooling.

Nonlinear response and threshold identification for arid ecosystem resilience to coupled stressors from extreme climate events and anthropogenic activities.

Cowpea (Vigna unguiculata (L.) Walp.), a globally important legume and high-quality plant protein source (Jayathilake et al. 2018), is widely cultivated in arid and semi-arid tropical zones. In March 2025, a cowpea plantation in Chengmai County, Hainan Province, China (110.168808°E, 19.735978°N) showed unusual wilting, with over 30% disease incidence. Initial symptoms included irregular, dark brown dry necrotic lesions on stem bases and nodes, expanding bidirectionally, followed by leaf yellowing and plant death. Longitudinal sections revealed browned vascular bundles and partially occluded xylem vessels. Five typical diseased samples were collected. Stems were thoroughly rinsed with sterile water, and small stem fragments (4 × 4 mm) were excised from the lesion periphery. These fragments were surface-sterilized with 70% ethanol and 3% NaClO, rinsed three times with sterile water, and then cultured on potato dextrose agar (PDA) at 28 °C in the dark for 7 days. After purification via single-spore isolation and incubation under the same conditions (28 °C in the dark on PDA) for 7 days, the colonies displayed taupe-grayish centers grading to white margins; their reverse sides featured white margins, yellowish-brown inner rings, and dark brown centers. The mycelia were dense and cottony-flocculent. Conidia were solitary or catenate, straight to curved, obclavate to cylindrical, with 0-4 pseudosepta, measuring 15.4-114.4μm × 4.7-11.05μm. Their morphological characteristics aligned with those of Corynespora cassiicola (Pan et al. 2024). The internal transcribed spacer (ITS) region and β-tubulin gene of isolate CM01 were amplified using the primer pairs ITS1/ITS4 (White et al. 1990) and Bt2a/Bt2b (Glass et al. 1995), respectively. BLAST analysis showed that the ITS sequence (GenBank accession no. PX307421) and β-tubulin gene sequence (GenBank accession no. PX868915) of the isolate shared 100% identity with the corresponding sequences of C. cassiicola (KU204615, PP419028). Pathogenicity was confirmed using one-week-old cowpea seedlings. Stems were punctured and inoculated with 5-mm mycelial plugs; controls received sterile PDA plugs. Each treatment was set with 5 replicates. Seedlings were incubated in a growth chamber (12-hour photoperiod, 25 ± 2°C, 90% relative humidity). Inoculated plants developed dark brown lesions at 3 days post-inoculation, with lesions gradually expanding. After 14 days, vascular browning, leaf curling, yellowing, abscission, and stunting were observed; controls remained asymptomatic. Re-isolated fungi from lesions matched the original isolate (CM01) in morphology, fulfilling Koch’s postulates. It has been reported that C. cassiicola can cause leaf spot disease in many plant species, including cowpea (Li et al. 2014). However, to our knowledge, this is the first report of stem rot caused by C. cassiicola on cowpea in China. These findings not only expand our understanding of the pathogenicity of C. cassiicola on cowpea but also serve as a critical reference for cowpea disease monitoring and management strategies in China.

The watering of pasture lands is a key condition for the sustainable development of livestock farming in the arid and semi-arid zones of southern Kazakhstan. This issue is particularly acute in the southern regions of the country, where there is a shortage of surface water sources and a significant portion of pastures is used extensively due to underdeveloped water supply infrastructure. One of the promising solutions to this problem is the use of groundwater for pasture irrigation and year-round livestock watering. The aim of this study is to assess the current state of water supply for pasture areas in southern Kazakhstan and to identify the potential for the sustainable use of groundwater. The article examines the natural-climatic and hydrogeological conditions of the region, analyzes spatial differences in water resource availability, and presents the results of field research. The study is based on scientific and technical materials from research conducted by the U.M. Akhmedsafin Institute of Hydrogeology and Geoecology in 2024. During field expeditions, route surveys of pasture lands were carried out, covering zones with varying degrees of water availability. Water samples were collected from wells and boreholes, followed by hydrogeochemical analysis under laboratory conditions. The results made it possible to determine the suitability of groundwater for livestock watering, to identify territorial differences in hydrogeological conditions, and to outline directions for improving the pasture watering system.

Impact of vegetation cover change on vegetation resilience in arid and semi-arid zones: a case study of Mu Us Sandy Land

The Tianshan–Pamir mountain region, serving as the core “water tower” for countries in Central Asia east of the Aral Sea, is a critical bulwark for sustaining downstream socioeconomic systems. However, constrained by complex topography and harsh climatic conditions, this region suffers from a severe scarcity of long-term, continuous hydrological observation data. This study focuses on a typical data-scarce mountainous area, coupling UAV and satellite imagery-based (e.g., Landsat/Sentinel) flow inversion with a hybrid spatial regionalization method—integrating spatial proximity, basin similarity, and regression-based hydrograph reconstruction—to quantitatively estimate long-term discharge time series. The results indicate that, for the validation of instantaneous discharge inversion, the Nash–Sutcliffe efficiency coefficient (NSE) at 29 river cross-sections was consistently greater than 0.80, with the coefficient of determination (R2) reached 0.94 (p < 0.01). Subsequently, for the long-term discharge series reconstructed using the regionalization method, the NSE values at three representative verification sites—each corresponding to a distinct basin type—were 0.88, 0.84, and 0.86, respectively. These findings exhibit higher precision compared to direct temporal upscaling, confirming the reliability of the regionalization method across varying temporal scales. An analysis of monthly discharge trends from 1989 to 2020 revealed a decreasing trend in the discharge of glacier-dominated rivers, with an average rate of change of −2.89 ± 2.54% (p < 0.05); the Pamir Plateau experienced the largest decline (−4.89 ± 6.58%), which is closely linked to large-scale glacial retreat within the basins. Conversely, the discharge of non-glacier-dominated rivers showed an increasing trend, with a multi-year average rate of change of +0.32 ± 8.43% (n.s.), primarily driven by shifts in precipitation and vegetation cover. This research introduces a new approach for hydrological monitoring in data-scarce regions and provides essential data and methodological support for water resource management decisions in arid zones.

The spatiotemporal evolution of drought patterns has drawn growing attention, particularly in the Yellow River Basin of northern China. However, the previous studies have primarily focused on unidirectional drought propagation. We extended the three-dimensional connectivity identification method to quantify the migration direction and distance between the centroids of drought initiation and termination, thereby improving the tracking and measurement of typical drought event trajectories. Furthermore, we systematically investigated the bidirectional dependencies and propagation characteristics among meteorological, hydrological, and agricultural droughts using Granger causality testing, drought propagation rate, and Maximum Cross-Correlation methods. The results illustrate that meteorological droughts were mainly in the middle-upper reaches, hydrological droughts in arid zones and upstream mountains, and agricultural droughts in semi-arid regions from 1981 to 2022. Hydrological droughts showed the longest migration distance. However, all drought types followed more complex pathways after 2010. Hydrological and agricultural drought exhibited consistent bidirectional dependence basin-wide. Propagation rates were generally high for meteorological-hydrological links except in upstream mountains, and notably strong for meteorological-agricultural propagation in the central-southern Wei River Basin. Seasonally, meteorological drought significantly impacted streamflow in spring and autumn, with hydrological drought lagging by 1–2 months across 72.4% of the basin. Agricultural systems responded within 1–5 months in summer and autumn. Hydrological-agricultural propagation showed similar seasonal patterns, with faster response from hydrological to agricultural drought (1–3 months) than the reverse (1–4 months).

Global greening is typically regarded as an ecosystem amelioration signal. However, recent studies document opposing trends where greening is accompanied by declining vegetation resilience. This study uses satellite and reanalysis data (2001–2022) to characterise the synchronous and asynchronous trends of global vegetation greenness (kernel Normalised Difference Vegetation Index, kNDVI) and resilience (lag-1 autocorrelation, AR1), employing ridge regression to identify hydroclimatic drivers. Results reveal that 41.8% of the global land surface, mainly in hydrothermally abundant humid regions, exhibited greening amidst declining resilience. Conversely, 35.9% of regions, predominantly in arid and semi-arid zones, showed synergistic increases in both greenness and resilience. These divergent trajectories stem from distinct hydroclimatic controls. In arid regions, precipitation simultaneously governs vegetation growth and resilience, driving their synergistic improvement. In humid regions, temperature dominates greening, whereas resilience remains constrained by precipitation and potential evapotranspiration, creating a trade-off. This study unmasks the latent risk of diminishing resilience hidden behind global greening, offering insights into the hydrological regulation of ecosystems under changing climates.

Semi-arid and arid zones have been largely overlooked in ecosystem services (ES) research. Here we reveal the diversity of ES in the Huasco River Basin (Atacama Region, Chile) and conduct a non-economic valuation based on semi-structured interviews (n = 201). We identified the ES considered most important by local residents and classified the arguments they used to justify their importance into three broad value types (intrinsic, instrumental and relational). We further examined how these value types relate to respondents’ general motivations. Water for agriculture emerged as the most frequently mentioned benefit, followed by recreation and food from traditional farming systems. Cultural ES such as sense of place and identity with the territory were also highly valued highly. Respondents articulated intrinsic instrumental and relational arguments when explaining why these ES matter to them. Respondents who scored higher on environmental justice motivation expressed significantly more relational arguments. Our pluralistic valuation approach highlights opportunities for interdisciplinary collaboration between researchers and local communities in complex, conflict-prone socio-ecological systems.

Fruit orchards are vital in delivering both economic and environmental services, yet their potential for carbon sequestration remains underexplored. Estimating carbon sequestration is important in semi-arid regions where vegetation cover is sparse; the perennial biomass adds litter inputs that enhance soil carbon storage and improve soil fertility. Quantifying carbon sequestration provides valuable insights into the role of fruit-based orchards in climate change mitigation in fragile ecosystems, thereby contributing to sustainable ecosystem services. The present investigation was carried out in different fruit orchards, viz. Ficus carica, Cordia myxa, Citrus limon, Citrus jambhiri and Aegle marmelos at ICAR-Central Arid Zone Research Institute, Regional Research Station, Pali Marwar, Rajasthan, India. Since fruit is an economic part, a non-destructive method based on tree dimensions (tree height and diameter) was used for biomass and carbon estimation. The results revealed significant differences among different species of fruit orchard (p < 0.001). C. myxa (29.28 ± 14.18) and A. marmelos (27.04 ± 9.60) recorded total carbon stock (kg tree-1) on par with each other. Pearson correlation coefficient indicates that tree height is positively correlated with above-ground biomass (AGB) and carbon stock (0.98). Among the five fruit orchards, Soil organic carbon (SOC) was highest in C. myxa irrespective of depth (8.45 Mg ha-1). C. myxa and A. marmelos are indigenous fruit tree species that can serve as potential carbon sinks and may be promoted for farmer adoption through supportive policies in the arid and semi-arid regions of Rajasthan.

Grasslands, covering over 40% of terrestrial land surfaces, play a critical role in regional water cycling through their greening processes. However, the decoupling mechanisms between grassland greening and water availability (WA) changes across the Northern Hemisphere, along with their future trajectories, remain poorly understood. Here, we integrated multi-source satellite observations with CMIP6 model ensembles to systematically assess the spatiotemporal evolution and trend divergence of leaf area index (LAI) and WA across Northern Hemisphere grasslands from 2000 to 2100. Our results showed that grassland LAI exhibited sustained growth during 2000–2020, with 55.28% of regions showing significant increasing trends. However, 73.67% of grassland regions experienced declining WA during the historical period, revealing widespread decoupling between grassland greening and water deficit. Future scenario projections indicated a reversal to increasing WA trends, with 57.51% of regions showing significant increases under SSP5–8.5. Furthermore, 61.87% of grasslands exhibited greening-driven drying (GDD) characteristics during the historical period, while greening-driven wetting (GDW) regions were projected to expand to 72.44% in the future. Analysis along aridity gradients revealed that humid zones contributed most prominently to LAI and WA changes. Mechanistic decomposition demonstrated that grassland WA changes shifted from precipitation-dominated control (53.60%) in the historical period toward a regime jointly governed by precipitation dominance and coupled precipitation–evapotranspiration drivers in the future. Concurrently, the dominant factor controlling grassland greening transitioned from vapor-pressure deficit (VPD) to temperature (TEM) control. Additionally, driving factors exhibited pronounced differentiation patterns along aridity gradients during the historical phase: arid zones were dominated by soil moisture (SM) and semi-arid zones displayed dual control by SM and VPD, while humid zones were governed by coupled TEM-VPD regulation. This study reveals the divergent trends between grassland greening and WA and unravels their driving mechanisms, offering important scientific evidence for formulating regionally differentiated ecological water resource management strategies.

The Australian continent underwent a series of dramatic climate changes during the Cenozoic, which impacted the evolutionary history and distribution of many groups of organisms. Up to now, few studies have explored the drivers of diversification and the processes that generated and maintained biodiversity in Australia. Here, we used the Australian endemic Eurepini crickets as a model system to investigate the impact of paleoenvironmental changes on the diversification of Australian lineages with a series of state-of-the-art macroevolutionary models. We inferred an Early Eocene origin of Eurepini in current Northern Australia, with the majority of descendant lineages diversifying in situ. We detected a drastic drop in diversification rate at the beginning of Pleistocene. Diversification rates of Eurepini declined with increasing aridity and decreasing temperature. Diversification rate heterogeneity was linked to contrasting geographic distributions: the arid-adapted lineages diversified at a much lower rate than their mesic-distributed counterparts. The drastic environmental changes that occurred from the Miocene onwards were likely detrimental to dispersal of Eurepini lineages, slowing down their diversification during the Pleistocene. The tribe likely suffered substantial diversity losses in the arid zone during progressive aridification of Australia. Our study highlights the importance of paleoenvironmental changes in shaping diversification dynamics of Australian lineages.

Precise spatiotemporal monitoring of soil moisture is fundamental to the efficient regulation and sustainable utilization of agricultural water resources in arid and semi-arid irrigation districts. This study focuses on the Yichang Irrigation District within the Hetao Irrigation Area to elucidate the spatiotemporal dynamics of surface soil moisture during the crop growing season. Multi-year Landsat 8/9 remote sensing imagery (2022–2024) was integrated with the Temperature Vegetation Dryness Index (TVDI) framework to construct two feature spaces, namely Normalized Difference Vegetation Index–Land Surface Temperature (NDVI–LST) and Enhanced Vegetation Index–Land Surface Temperature (EVI–LST). A dual-index complementary inversion strategy was applied for soil moisture estimation, and the outputs were validated against Soil Moisture Active Passive (SMAP) soil moisture products and MOD16 evapotranspiration products. Results indicated that the dry edges of the feature spaces derived from both vegetation indices exhibited double-inflection-point characteristics, with optimal fitting intervals located between the inflection points. The inflection point positions shifted dynamically with variations in crop coverage. During bare-soil and low-vegetation-coverage periods (May, June, and September), the minimum thresholds for low NDVI and EVI values were 0.07 and 0.06, respectively, whereas during high-vegetation-coverage periods in July and August, the minimum thresholds for both indices increased to 0.15. NDVI demonstrated superior performance during May, June, and September, whereas EVI exhibited greater advantages during active crop growth periods in July–August. The optimized model achieved robust inversion accuracy, with a validation R2 of 0.81 for the measured soil moisture in the 0–20 cm layer on 12 May 2024. The inversion results exhibited strong correlations with the SMAP soil moisture products (R2 = 0.663 during low crop coverage; R2 = 0.625 during high crop coverage) and MOD16 evapotranspiration data (R = 0.751). The spatiotemporal patterns of soil moisture were distinctly discerned. Following spring irrigation in May, abundant moisture in certain areas resulted in bimodal distribution patterns in the inversion results. June exhibited the lowest soil moisture content across the study area, with arid zones making up 36.67% of the total area. From July to August, concentrated precipitation coupled with summer irrigation reduced the proportion of extremely arid zones to below 0.98%.

This study shows that the photosynthesis of Arctic terrestrial plants is more vulnerable and sensitive to heatwaves’ impacts than plants in other European climate zones. The results of this study indicate distinct effects of heatwaves among different climate zones in Europe (2009–2017). The Arctic climate zone shows a steeper decline in photosynthesis during heatwaves, as revealed by geographically and temporally weighted regression analysis based on biophysical factors such as the Normalized Difference Vegetation Index and Leaf Area Index, compared to arid, temperate, and cold climate zones. As Arctic temperatures continue to rise, it would lead to photosynthetic inhibition from Arctic terrestrial plants, irreversibly turning them into one of the largest CO2 sources. The results of this study are expected to be a valuable reference as they provide European-wide quantitative evidence that global warming has caused comparably stronger negative consequences on the photosynthetic physiology of plants living in the Arctic compared to other climatic zones.