Water scarcity, particularly in arid and semi-arid regions, is a critical issue affecting forest management. This study investigates the effects of drought stress on the water requirement and morphological characteristics of two important tree species Turkish pine and Chinaberry. Using a factorial design, the study examines the impact of three age stages (one-year-old, three-year-old, and five-year-old plants) and three levels of drought stress on these species. Microlysimeters of varying sizes were employed to simulate different drought conditions. Soil moisture was monitored to show the effect of the various irrigation schedules. The study also calculated reference crop evapotranspiration (ET₀) using the PMF-56 method and developed plant coefficients (Kc) for the species. Results showed that evapotranspiration increased with soil moisture, peaking during summer and decreasing in winter. Turkish pine exhibited higher plant ET than Chinaberry, particularly among one-year-old seedlings. Drought stress significantly reduced evapotranspiration and water uses for both species, highlighting the importance of efficient water management in afforestation projects. The findings underscore the necessity of selecting drought-resistant species and optimizing irrigation practices to enhance the sustainability of green spaces in arid regions. These insights are crucial for improving urban forestry management and mitigating the impacts of water scarcity in Iran and similar climates globally.

The exploitation of timber has had a profound impact on tropical forest areas and their structures. This study assessed the effect of selective logging on natural regeneration and soil characteristics in post-loading bay sites at the Pra-Anum forest reserve in Ghana, West Africa. The results showed no difference in the number of species enumerated in the loading bays and the undisturbed area. More trees were observed in the RAT and RNT plots than in the undisturbed area. Relative to the RAT plot, species on the RNT and the undisturbed area were less diverse and less evenly distributed. Mean tree height, diameter, and basal area were higher in the RAT and RNT plots than in the undisturbed plots. Soil bulk density was lower in the RAT and undisturbed plot than in the RAT plot and increased with increased depth. Soil organic matter was 44% and 27% more in the undisturbed and RAT plots, respectively, than in the RNT plot and accounted for 84.75%, 83.97% and 45.33% of variations in soil bulk density, pH, and CEC. The study provides insight into the need to rehabilitate highly disturbed areas in forests, particularly the addition of topsoil on loading bays, skid trails, roads, and gaps after logging to improve the productivity of the forest soils.

In order to address severe siltation and enhance urban green spaces in Xianyang Lake, the research offers a sustainable solution by proposing an innovative integration of ecological dredging and landscape transformation. The key findings are as follows: Firstly, an ecological dredging mechanism was established by directly transporting sediment from Xianyang Lake to its central greenbelt, reducing dredging costs and environmental impact while creating a sustainable funding cycle through revenue from eco-tourism activities. Secondly, the landscape artistic conception of the central greenbelt was significantly improved by leveraging the natural distance between the lakeshore and the greenbelt, offering diverse viewing experiences and enhancing the cognitive abilities and urban life satisfaction of tourists. Thirdly, the project demonstrated substantial economic and social benefits, including revenue generation from paid activities like boat tours, increased public awareness of biodiversity through ecological education, and improved community well-being. The central greenbelt also enhanced the urban environment by improving air quality, mitigating the “heat island effect,” and providing habitats for wildlife. This integrated approach serves as a model for sustainable urban development, offering valuable insights for cities facing similar ecological challenges. Future research should focus on long-term monitoring to further evaluate the ecological and socio-economic impacts of such projects.

In Côte d’Ivoire, the government and its development partners have implemented a national strategy to promote agroforestry and reforestation systems as a means to combat deforestation, primarily driven by agricultural expansion, and to increase national forest cover to 20% by 2045. However, the assessment of these systems through traditional field-based methods remains labor-intensive and time-consuming, particularly for the measurement of dendrometric parameters such as tree height. This study introduces a remote sensing approach combining drone-based Airborne Laser Scanning (ALS) with ground-based measurements to enhance the efficiency and accuracy of tree height estimation in agroforestry and reforestation contexts. The methodology involved two main stages: first, the collection of floristic and dendrometric data, including tree height measured with a laser rangefinder, across eight (8) agroforestry and reforestation plots; second, the acquisition of ALS data using Mavic 3E and Matrice 300 drones equipped with LiDAR sensors to generate digital canopy models for tree height estimation and associated error analysis. Floristic analysis identified 506 individual trees belonging to 27 genera and 18 families. Tree height measurements indicated that reforestation plots hosted the tallest trees (ranging from 8 to 16 m on average), while cocoa-based agroforestry plots featured shorter trees, with average heights between 4 and 7 m. A comparative analysis between ground-based and LiDAR-derived tree heights showed a strong correlation (R² = 0.71; r = 0.84; RMSE = 2.24 m; MAE = 1.67 m; RMSE = 2.2430 m and MAE = 1.6722 m). However, a stratified analysis revealed substantial variation in estimation accuracy, with higher performance observed in agroforestry plots (R² = 0.82; RMSE = 2.21 m and MAE = 1.43 m). These findings underscore the potential of Airborne Laser Scanning as an effective tool for the rapid and reliable estimation of tree height in heterogeneous agroforestry and reforestation systems.