This study aimed to evaluate the synergistic effects of zinc sulfate and Pseudomonas spp. in terms of mitigating drought stress in maize (Zea mays L.) by analyzing physiological, biochemical, and morphological responses under field conditions. A two-year (2018-2019) field experiment investigated two irrigation levels (optimal and moderate stress) and twelve treatment combinations of zinc sulfate application methods (without fertilizer, soil, foliar, and seed priming) with zinc-solubilizing bacteria (no bacteria, Pseudomonas fluorescens, and Pseudomonas aeruginosa). Drought stress significantly reduced chlorophyll content, increased oxidative damage, and impaired membrane stability, leading to a 42.4% increase in electrolyte leakage and a 10.9% reduction in leaf area index. However, the combined application of zinc sulfate and P. fluorescens, and P. aeruginosa mitigated these effects, with seed priming showing the most significant improvements. Specifically, seed priming with zinc sulfate and P. fluorescens increased catalase activity by 76% under non-stress conditions and 24% under drought stress. Principal component analysis revealed that treatments combining zinc sulfate and P. fluorescens, and P. aeruginosa were strongly associated with improved chlorophyll content, carotenoid content, and grain yield while also enhancing osmotic adjustment and antioxidant enzyme activity. These findings highlight the potential of the use of zinc sulfate and P. fluorescens as well as P. aeruginosa as sustainable strategies for enhancing maize drought tolerance, mainly through seed priming and soil application methods.

Using infrared thermography (IRT) has been proven as an effective technology for early damage detection within the superstructure/substructure of the ballasted railway tracks. Performing statistical processing and integrating principle component analysis (PCA) underpinned by extensive data sources of infrared imaging technology can effectively detect complex features exhibiting temperature variation. The present study employs these processing techniques on thermal images to investigate the drainage health of railway ballast layer using IRT technology. Specifically, clean and clay-fouled ballast specimens are prepared to study the effect of contamination/fouling in ballast layer (porous granular media) on water retention (indicated by water level) during severe rainfall intensity. IRT is utilized to monitor the water level as the indicator of ballast layer drainage health condition. Results show that the IRT image-processing technology confirms the capability of IRT for detecting water surface/water retention based on the thermal images captured from ballast specimen surface. In addition, an appropriate time for monitoring via IRT is after heavy rainfall upon which the water retention in the ballast layer can be more effectively detected. Particularly, presence of water and fouling material among ballast particles results in lower and more uniform surface temperature compared to dry or clean ballast specimens.

Plants activate physiological responses against salinity stress through hormone signaling pathways such as melatonin (M) and methyl jasmonate (MeJ). These hormones trigger defense responses, but comparing their individual and combined effects under salt stress has not been studied. This research investigates defense responses in tomato plants induced by 100 mu M of M and MeJ, along with their combined application (MeJ+M, 100+100 mu M) under non-stress, threshold (0.9 g NaCl kg-1 soil) and severe (1.8 g NaCl kg-1 soil) salinity conditions. Compared to melatonin, MeJ application caused adverse effects, including chlorophyll degradation (34.2 %), root inhibition (17.2 %), and elevated H2O2 (28.9 %), O2-center dot (33.7 %), and malondialdehyde (14.3 %) in the plant under non-stress conditions. Evaluation of the MeJ+M treatment in non-stress conditions indicated that M prevented MeJ-induced damage. Besides, the optimal potassium uptake and plant growth were obtained in the MeJ+M treatment under non-stress and threshold salinity levels. Phytohormones application increased enzymatic antioxidant activity (superoxide dismutase, catalase, ascorbate peroxidase, and peroxidase), modified the activity of phenylalanine ammonia-lyase and polyphenol oxidase, and consequently boosted non-enzymatic antioxidants (phenolic, flavonoid, and anthocyanin content), resulting in a significant reduction of damage from severe salinity stress. However, due to their almost similar physiological changes induced by MeJ, M, and MeJ+M, these treatments were not superior compared to each other in severe stress. Thus, owing to the disruption of the normal morpho-physiological processes in non-stress conditions by MeJ, M can be considered a safer treatment for practical usage. Additionally, the MeJ+M application can not only optimize antioxidant protection under stress conditions but also stimulate plant growth under non-stress conditions.

Wildfires play a dual role in ecosystems by providing ecological benefits while posing catastrophic events; they also inflict non-catastrophic damage and yield long-term effects on biodiversity, soil quality, and air quality, among other factors, including public health. This study analysed the key determinants of wildland fires in Spain using openly available spatial data from 2008 to 2021, including fire perimeters, bioclimatic variables, topography, and socioeconomic datasets, at a resolution of 1 km(2). Our methodology combined principal component analysis (PCA), linear regression analysis, and one-way analysis of variance (ANOVA). Our findings show that scrub/herbaceous vegetation (average 63 +/- 1.45% SE) and forests (average 19 +/- 0.76% SE) have been highly susceptible to wildfires. The population density exhibited a robust positive correlation with wildfire frequency (R-2 = 0.88, p < 0.0001). Although the study provides insights into some fire-related climatic drivers over Spain, it includes only temperature- and precipitation-based variables and does not explicitly consider fuel dynamics. Therefore, a more advanced methodology should be applied in the future to understand the local specifics of regional wildfire dynamics. Our study identified that scrub/herbaceous areas and forests near densely populated regions should be prioritised for wildfire management in Spain, particularly under changing climate conditions.

The literature shows that a circular economy can benefit some sectors such as the construction industry. This sector demands huge amounts of raw materials and produces waste when buildings and structures are demolished. This paper explores the possibility of manufacturing at industrial scale paving blocks using different types of construction and demolition wastes as aggregates, without modifying the commonly used industrial conditions. A total of four different recycled aggregates were used in this research. Both natural and recycled aggregates have been characterized. The dosages were optimized (three different formulations). Prefabricated tests have been carried out on the products manufactured in industrial plants and the evolution of mechanical properties over time has been analysed. The results obtained were analysed statistically by applying the principal component analysis (PCA) method. To ensure the security of the elements manufactured, the ionic leaching of the materials used as recycled aggregate and of the elements produced has been tested. The main implications of this research on the construction industry show that the majority of recycled aggregates used could replace 25% of the natural aggregate in manufactured precast concrete, that the properties of the aggregates should be taken into account in the different standards and that all paving blocks manufactured in this study can be considered environmentally safe (no risk of leaching) according to the Netherland Soil Quality Decree. Therefore, it is evident that it is possible to manufacture on an industrial scale paving blocks with mixed recycled aggregates, concrete and ceramic in nature, both with the fine and coarse fractions that meet the requirements of its reference standard UNE-EN 1338 and the Netherland Soil Quality Decree that evaluates environmental risks due to leaching.

The hydrology of the Third Pole, Asia's freshwater tower, has shown considerable sensitivity to the impacts of climate change and human interventions, which affect the headwaters of many rivers that originate therein. For example, the Yangtze River has its basin (YRB) experiencing wetness of terrestrial water storage (TWS), whose rainfall seems to be the primary source as inferred from the previous studies. Consequently, it is crucial to understand the contributions of each TWS's sub-domain - i.e., groundwater (GWS); total water content (TWC) stored as soil moisture, ice/snow, and canopy; and the surface water (SWS) storages - on YRB's wetness. Hence, SWS, from altimetry and imagery satellites, and TWC, from Global Land Data Assimilation System, are inverted considering the same basis function as for TWS from the Gravity Recovery and Climate Experiment, which account for the differences in the resolutions inherent in each product. Furthermore, a tie-in signal approach is used to fit the temporal patterns of GWS, TWC, and SWS to TWS (i.e., the observations). Results show improvements in the reconstructed GWS series concerning standard deviation, correlation coefficient, and Nash-Sutcliffe efficiency of 22%, 27%, and 120%, respectively, regarding the use of the TWS-budget equation. The reconstructed time series of GWS, TWC, and SWS present an increase of 1.76, 2.69, and 0.14 mm per year (mm/yr) and that YRB loses water stored at its aquifers 55% of the time (regarding 2003-2016 period) based on the quantile function of storage (QFS). The QFS's slope shows that TWS has a fast and small storage potential w.r.t. GWS since inland waters and soil moisture reflect the dryness impacting TWS first. Despite the evidence of an increase of 19.05 mm/yr in annual precipitation, which seems to explain the bulk in TWS, further investigation to characterize controls on TWS memory within YRB is still necessary. (C) 2020 Elsevier B.V. All rights reserved.

分析了2003-2009年基于卫星观测的降水数据CMORPH、TMPA 3B42v6、中国科学院青藏高原研究所的融合数据ITPCAS和基于地面台站的APHRODITE(2003-2007)四套降水数据集在叶尔羌河上游流域的时空分布特征,并以这四套降水数据为驱动,利用VIC分布式水文模型对叶尔羌河上游流域的降水径流进行模拟.结果表明:在空间分布上,四套降水资料在叶尔羌河上游流域的差异较大,ITPCAS的空间分布与流域冰川的分布较一致,基于冰川区即为大降水区的基本认知,初步认为ITPCAS的空间分布比较合理;其次是TMPA 3B42v6和APHRODITE;在流域的年降水量和季节分配量上,由于缺乏高海拔地区的实测降水资料,无法准确回答各套降水资料在量级上是否合理;在时间序列上,四套降水资料与流域站点降水(库鲁克栏杆站和塔什库尔干站的平均降水)存在着不同程度的差异.但从整体上看,CMORPH数据在一定程度上能够反映流域的月降水变化过程,而APH-RODITE和ITPCAS只能在个别年份对流域的降水描述较好;在径流模拟上,卫星降水数据CMOR-PH显示了作为水文模型输入数据的较大潜力;而其他降...