Modelling Woody Vegetation Suitability in Saloum Delta Ramsar Site (West-Africa): Implications for Conservation and Land Restoration

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Woody vegetation is crucial in maintaining ecological balance, supporting biodiversity, and contributing to carbon storage. However, these ecosystems face increasing threats from deforestation, climate change, and human activities. Despite the current challenges, diagnostics and preliminary information for guiding regreening interventions to restore ecosystems are notably lacking. This study employed Species Distribution Models (SDMs) to predict the spatial distribution and suitability of four woody tree covers (Mangroves, Close Woodlands, Open Woodlands, and Plantations). In each woody cover, a hundred occurrence points were used. The study used machine learning approaches such as Random Forest (RF), MaxEnt, and Generalized Linear Models (GLM) to analyse the relationships between woody cover occurrence data and environmental predictors, including climate, soil properties, anthropogenic factors, and natural disturbances. Results indicate that Salinity is the most significant driver affecting all vegetation types, particularly mangroves. Rainfall strongly influences Close Woodlands and Plantations, while fire disturbances shape Open Woodlands. Predicted suitability maps reveal potential habitat suitability, indicating areas of high restoration potential and underscoring the need for targeted conservation and restoration strategies. Comparison between current coverage and the predicted suitability revealed the smallest gap in Mangroves to cover the optimum suitable area (3.47%) while substantial areas still exist for Close woodlands, Open Woodlands and Plantations with 5,49, 6,03 and 6,41, respectively. Findings from this study provide essential insights for sustainable land management, regreening policy initiatives, and woody ecosystem restoration planning in West Africa’s woody coastal areas. By integrating Geographic Information System (GIS) and ecological modelling, this research enhances decision-making for biodiversity conservation and climate resilience.

Examining Development Project Selection Difficulties in Digital Communication Companies: A Root Cause Analysis

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ABC, a leading company in communications technology, is facing challenges in developing a fair and unbiased process for selecting new ventures amid an increasing number of computer program development projects. In conditions where the industry faces many projects taking place simultaneously, but the number of available developers is limited, the process of managing and evaluating projects becomes increasingly complex. This results in a decrease in the level of customer satisfaction with the products and services the company provides. In addition, the company faced problems due to the unavailability of clear and consistent project evaluation guidelines. The lack of clear and consistent guidelines resulted in less efficient resource allocation and extended the duration of project completion. This research focuses on improving the decision-making process by using root cause analysis to identify key issues and their impacts. The methods used include surveys, semi-structured interviews, and root cause analysis to explore the core problems and needs of stakeholders. The results showed four main causes of weak project management and decision-making: technical, financial, administrative and strategic planning issues. Overall, the research provided insights into how these issues affected service performance, increased operational waste, reduced quality, and resulted in stakeholder dissatisfaction.

Conversion of Waste Cooking Oil into Biofuel through CeO₂-Based Oxide Catalysts (CeO₂-La₂O₃-NiO)

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The CeO₂-based oxide catalysts (CeO₂-La₂O₃-NiO) were successfully synthesized with different concentrations of microcrystalline cellulose (MCC). The resulting materials underwent characterization through various techniques, including TGA, XRD, FTIR, TEM, FESEM-EDX, and N₂ adsorption-desorption. XRD characterization revealed that the CeO₂ phase was a stable compound in all synthesized products. The semi-batch reactor was operated for 4 hours at 360 °C for the deoxidation reaction of used cooking oil using 1 wt% product catalyst. Deoxygenation occurred perfectly in the sample using BCOe-12.5 wt% MCC catalyst, resulting in 99% hydrocarbon selectivity and yielding 46% liquid product. These findings underscore the effectiveness of CeO₂-based oxides (CeO₂-La₂O₃-NiO) as promising catalysts for biofuel synthesis.

A Control Chart Based on Moving Average Model Functioned for Poisson Distribution

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A control chart used with MA control chart to track the number of faulty products or faults suggested. When the characteristics of quality of interest obey a Poisson distribution. A specified number of objects are observed at various time intervals in order to observe the number of non-conformities. By measuring ARLs under different sample sizes and parameters by considering ARLs in power, the output of the proposed chart is evaluated. It should be noted The proposed control chart seems to be more reliable than the traditional current control charts in detecting small adjustments in the manufacture process.