Bangladesh’s coastal regions are rich in saline water resources. The majority of these resources are still not being used to their full potential. In the southern Bangladeshi region of Patuakhali, research was conducted to investigate the effects of mulching and drip irrigation on tomato yield, quality, and blossom-end rot (BER) at different soil salinity thresholds. There were four distinct treatments applied: T₁= drip irrigation with polythene mulch, T₂ = drip irrigation with straw mulch, T₃ = drip irrigation without mulch, and T₄ = standard procedure. While soil salinity was much greater in treatment T₃ (1.19–8.42 dS/m) fallowed by T₄ (1.23–8.63 dS/m), T1 treatments had the lowest level of salinity and the highest moisture retention during every development stage of the crops, ranging from 1.28–4.29 dS/m. Treatment T₃ exhibited the highest soil salinity levels (ranging from 1.19 to 8.42 dS/m), followed by T₄ with a range of 1.23 to 8.63 dS/m. In contrast, T₁ treatments consistently maintained the lowest salinity levels (ranging from 1.28 to 4.29 dS/m) and the highest moisture retention throughout all stages of crop development. In terms of yield, drip irrigation with no mulch treatment (T₃) provided the lowest output (13.37 t/ha), whereas polyethylene mulching treatment (T₁) produced the maximum yield (46.04 t/ha). According to the study, conserving moisture in tomato fields and reducing soil salinity may both be achieved with drip irrigation combined with polythene mulch. The research suggests that employing drip irrigation in conjunction with polythene mulch could effectively preserve moisture in tomato fields and concurrently decrease soil salinity.

Afforestation is a main tool for preventing desertification and soil erosion in arid and semiarid regions of Iran. Large-scale afforestation, however, has poorly understood consequences for the future ecosystems in the term of ecosystems protection. The objective of the present study is to identify changes in soil properties following different intervals of planting of Ailanthus altissima (tree of heaven) in semiarid afforestation of Iran (Chitgar Forest Park, Tehran). For this purpose, sand, silt and clay ratios, bulk density, soil moisture, pH, electrical conductivity, phosphorus, potassium, magnesium, calcium, sodium, total soil N, and total carbon was measured. Our study highlighted the potential of the invasive trees by A. altissima, to alter soil properties along chronosequence. Almost all soil quality attributes showed a declining trend with stand age. A continuous decline in soil quality indicated that the present land management may not be sustainable. Therefore, an improved management practice is imperative to sustain soil quality and maintain long-term productivity of plantation forests. Thinning activity will be required to reduce the number of trees competing for the same nutrients especially in a older stand to protect forest soils.

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at the same spatial resolution as the optical sensors (5km here) and applied for drought analysis in the continental United States. A new refined model is proposed to include auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed soil moisture model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns. Currently, the USDM is providing a weekly map. Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively higher spatial resolution than those traditionally derived from passive microwave sensors, thus drought maps based on soil moisture anomalies can be obtained on daily basis and made the flash drought analysis and monitoring become possible.

This study examines the aggregate consumption function of Saudi Arabia from 2000 to 2022, focusing on identifying key determinants of household consumption and evaluating the impacts of disposable income, household wealth, government expenditure, interest rates, and oil revenues. the research uses advanced econometric methods, including the autoregressive distributed lag (ARDL) model and Johansen cointegration test, to analyze the relationships among these variables. the findings reveal that disposable income, household wealth, and government expenditure significantly and positively influence consumption, whereas interest rates show a negative correlation. oil revenues also play a critical role, reflecting the country’s economic reliance on oil. the study highlights the necessity for economic diversification to reduce the impact of oil price volatility on household income and consumption stability. The results offer crucial insights for policymakers, emphasizing the need for strategies that enhance household income and wealth, maintain robust public sector spending, and effectively manage interest rates. these findings also support the importance of consistent and predictable income sources for sustaining consumption. additionally, this study suggests directions for future research, including developing sophisticated forecasting models to predict consumption trends and exploring other influencing factors such as demographic shifts and technological progress.

Relying on the D-Vine copula model, this paper delves into the hedging capabilities of Brent crude oil against the exchange rate of oil-exporting and oil-importing nations. The results affirm Brent crude oil’s role as a safeguard and a refuge against the fluctuations of major currencies. Furthermore, we reaffirm that oil retains its robust hedging and safe-haven attributes during times of crisis, with currency co-movements across all countries exhibiting greater correlation than during the entire dataset. Additionally, our empirical findings highlight an unusually positive correlation between Brent crude oil and the Russian exchange rate during the Russia-Ukraine conflict, demonstrating that oil functions as a less effective hedge and a less dependable refuge for the Russian exchange rate in such geopolitical turbulence.

Root turnover is a key process of terrestrial ecosystem carbon cycle, which is of great significance to the study of soil carbon pool changes and global climate change. However, because there are many measurement and calculation methods of root turnover, the results obtained by different methods are quite different, and the current research on root turnover of forest ecosystem on the global regional scale is not sufficient, so the change law of root turnover of global forest ecosystem is still unclear. By collecting literature data and unifying the calculation method of turnover rate, this study integrates the spatial pattern of fine root turnover of five forest types in the world, and obtains the factors affecting fine root turnover of forest ecosystem in combination with soil physical and chemical properties and climate data. The results showed that there were significant differences in fine root turnover rate among different forest types, and it gradually decreased with the increase of latitude; the turnover rate of fine roots in forest ecosystem is positively correlated with annual average temperature and annual average precipitation; fine root turnover rate of forest ecosystem is positively correlated with soil organic carbon content, but negatively correlated with soil pH value. This study provides a scientific basis for revealing the law and mechanism of fine root turnover in forest ecosystem.