Bioinoculants are increasingly used in land restoration programs to alleviate environmental stress during tree establishment and to enhance vegetation recovery in degraded ecosystems. However, their effects on native soil microbiota remain insufficiently understood, particularly in highly vulnerable environments, limiting their large-scale application. In salt-affected lands of Senegal, restoration strategies rely on Casuarinaceae species inoculated with a multi-kingdom bioinoculant composed of salt-tolerant arbuscular mycorrhizal fungi and nitrogen-fixing bacteria. While this strategy successfully enhanced tree growth and understory vegetation, its consequences for soil microbial diversity and functions have never been assessed. The objective of this study was to assess whether bioinoculation alters soil microbiota and to determine the relative influence of bioinoculation compared with salinity and host plant identity. We hypothesized that bioinoculation reshapes both soil bacterial and fungal microbial communities, with implications notably on soil nutrient cycling, but that these effects are constrained by salinity and Casuarinaceae species. Our results show that bioinoculation reduced overall fungal diversity without affecting rare taxa, whereas bacterial diversity was primarily driven by salinity and host plant identity, with effects largely confined to dominant bacterial groups. Functional predictions revealed marked shifts, with bioinoculation associated with a decrease in potential bacterial pathogen guilds, while increasing salinity promoted potential fungal pathogen guilds. Bacterial-mediated nitrogen cycling responded jointly to salinity and host plant identity, whereas nitrogen-fixing bacterial taxa were specifically promoted by bioinoculation. Overall, our findings demonstrate that bioinoculation can significantly modify soil microbial diversity and predicted functions in salt-affected soils, but that its effects may be overridden by strong environmental constraints and host plant effects. These results highlight ecological trade-offs associated with bioinoculant use and emphasize the need to integrate soil microbial responses into sustainable salt-affected land restoration strategies.
Accurate short-term air quality forecasting is urgently needed in African megacities. Chronic PM2.5 pollution threatens public health in these cities. At the same time, ground-based monitoring infrastructure remains sparse. This study develops and evaluates an operational 24-h PM2.5 forecasting system for the low-income housing (HLM) district of Dakar, Senegal. The site represents a high-exposure urban–industrial environment. Daily PM2.5 concentrations from 2019 to 2024 (mean = 274.71 µg/m3) were predicted using four ensemble machine learning (ML) models: Random Forest (RF), Extra Trees Regression (ETR), Extreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost). Predictor variables included ERA5-Land meteorology, aerosol optical depth (AOD) from the Copernicus Atmosphere Monitoring Service (CAMS), and Sentinel-5P tropospheric columns (NO2, CO, SO2). CatBoost achieved the highest performance on the independent 2024 test set (R2 = 0.931, RMSE = 11.50 µg/m3, MAE = 7.51 µg/m3). Shapley Additive exPlanations (SHAP) analysis identified AOD as the dominant predictor, followed by lagged PM2.5, relative humidity (RH), seasonality, and precipitation (PRECIP), reflecting the combined influence of Saharan dust transport, hygroscopic growth factor (HGF), wet deposition, and Harmattan–monsoon dynamics (see the “Physical interpretation of feature importance and SHAP analysis” section for full interpretation). External forcing dominated over local emission persistence, confirming that accurate 24-h predictions can be issued without any real-time ground-based PM2.5 input. Relying exclusively on open-access data and requiring minimal computational resources, the framework is scalable to other Sahelian urban contexts with similar monitoring constraints. These findings demonstrate that physically interpretable ML can transform sparse ground networks into actionable public health intelligence.
Groundwater serves as the primary supply source for socioeconomic activities in the Casamance region (south of Senegal), yet hydrogeochemical and water quality characteristics as well as flow patterns of groundwater at a regional scale are largely undocumented. This study aims to contribute to the understanding of hydrogeochemical processes of mineralization and to the hydraulic functioning of the Continental Terminal (CT) and Oligo-Miocene (OM) aquifer systems. Field campaigns were conducted in December 2021 (beginning of the dry season) and May 2024 (end of the dry season) to collect water samples from dug wells (n = 93), boreholes and piezometers (n = 46), and surface water (n = 3) for major and minor ions chemistry, water isotopes (δ2H, δ18O, 3H) and carbon isotopes (δ13C and 14C) analyses. The results reveal that silicate weathering and carbonate dissolution, together with ion exchange, are responsible for the groundwater mineralization in both aquifers with dominating Ca–HCO₃, mixed-HCO₃, and Na–Cl water types. The Comprehensive Pollution Index (CPI) method used to evaluate anthropogenic influence reveals that the pollutant levels in the CT aquifer are moderate to high, while the OM aquifer contains high-salinity (TDS = 2346 mg/L) groundwater derived from residual marine waters. Stable isotope distributions in the OM aquifer reveal two distinct patterns: enriched values (from −6.68 to − 4.67 ‰ δ1⁸O) in the confined part of the aquifer and depleted values between − 6.85 and − 5.14 ‰ δ1⁸O in the unconfined part. Variations in stable isotope values indicate recharge under different climatic conditions and mixing with seawater, while 3H content indicates recent recharge in the CT aquifer and sub-modern water in the OM aquifer. δ13C and 14C correlation reveals a rise in carbon activity from the confined to the unconfined aquifer and an active isotopic exchange with the carbonate fraction of the OM aquifer matrix. These findings provide the first regional-scale insight into the functioning of the CT and OM aquifer systems. They will guide future interventions in water supply projects as well as in securing reliable and high-quality water for local communities and supporting water resource management in the Casamance region.
Freshwater lenses encompassed in saline groundwater systems can be critical for society and ecology. Application of geophysical methods to discriminate the fresh/saline interface is becoming routine. However, without borehole control, relying on individual geophysical methods can lead to ambiguous interpretation, whether it is between saline pore fluids and clays, freshwater saturated and unsaturated sands, or simply fresh/saline water itself. In this study, we augmented transient electromagnetic (TEM) profiles with surface nuclear magnetic resonance (SNMR) in two regions of Senegal to uniquely identify and map freshwater lenses. The use of steady-state SNMR protocols allowed for dense coverage and robust estimates of the T2 relaxation time, providing a detailed characterization of the aquifer systems in the absence of borehole control. Specific to steady-state SNMR, these measurements marked the first successful demonstration operating in the relatively low geomagnetic fields associated with equatorial regions. Joint interpretation of the TEM and SNMR showed 10-20 m of freshwater perched on a saline aquifer base in one region, whereas the other showed saline groundwater extending over 6 km inland from the saline river. These case studies demonstrate the utility of a multi-method approach in data-scarce regions.
This paper aims to assess the impact of the National Family Security Grant Program (PNBSF) on the well-being of rural households in Senegal. The methodological approach was conducted in two stages. In the first stage, a difference-in-differences (DID) model based on surveys that were carried out in 2012 and between 2019 and 2021 was used. In the second stage, another cash transfer program called the Social Protection Initiative for Vulnerable Children (IPSEV in French) was incorporated into the model. The sample comprises 5958 households spread across the eight districts of the Linguère and Matam regions. The results show that households benefiting from the PNBSF are less likely to engage in cereal crop cultivation and more likely to increase the size of their small ruminant herds as a strategy to improve household welfare. However, the impact is more significant with the addition of the IPSEV program on household welfare. In terms of economic policy implications, the government must set up a structure that will coordinate all social programs and develop alliances with other projects or programs aimed at strengthening the economic well-being of households.
