Search Results (4)

Understanding seasonal patterns in mammals’ diversity and spatial distribution is vital for effective biodiversity conservation. This study examines seasonal variations in mammal diversity and distribution in the Pénéssoulou Classified Forest (northwest Benin). We hypothesized that (i) species richness and abundance are highest during the rainy season due to greater water and food availability; and (ii) small mammals exhibit spatial clustering, whereas large mammals are more spatially dispersed. We carried out negative binomial regression to analyze the effects of season, vegetation type, and proximity to waterholes on species richness. Spatial patterns were analyzed using Moran’s I index across size categories. We found lower species richness in the dry season (β = −0.812 ± 0.375, p = 0.030), which supports our hypothesis and is likely driven by increased resource availability. Contrary to our expectation, small mammals tended to be more dispersed during the rainy season, while larger mammals showed greater dispersion in the dry season. Significantly lower species richness was observed in gallery forests (β = −2.794 ± 1.144, p = 0.015), probably due to seasonal flooding, which limits access to resources. Our findings underscore the importance of incorporating seasonal and habitat-specific variables into wildlife monitoring and management. Full article

Quantitative precipitation estimation using polarimetric radar in attenuation-prone frequency (X-band) in tropical regions characterized by convective rain systems with high intensities is a major challenge due to strong attenuations that can lead to total signal extinction over short distances. However, some authors have addressed this issue in Benin since 2006 in the framework of the African Monsoon Multidisciplinary Analysis program. Thus, with an experimental setup consisting of an X-band polarimetric weather radar (Xport) and a network of rain gauges, investigations have started on the subject with the aim of improving rainfall estimates. Based on simulated polarimetric variables and using a Multilayer Perceptron artificial neural network, several bi-variable and tri-variable algorithms were assessed in this study. The data used in this study are of two categories: (i) simulated polarimetric variables (Rayleigh reflectivity $Z$, horizontal attenuation $A_h$, horizontal reflectivity $Z_h$, differential reflectivity $Z_{dr}$, and specific differential phase $K_{dp}$) and rainfall intensity (R) obtained from Rain Drop Size Distribution (DSD) measurements used for algorithm evaluation (training and testing); (ii) polarimetric variables measured by the Xport radar and rainfall intensity measured by rain gauges used for algorithm validation. The simulations are performed using the T-matrix code, which leverages the scattering properties of spheroidal particles. The DSD measurements taken in northwest Benin were used as input for this code. For each spectrum, the T-matrix code simulates multiple variables. The simulated data (first category) were divided into two parts: one for training and one for testing. Subsequently, the best algorithms were validated with the second category of data. The performance of the algorithms during training, testing, and validation was evaluated using metrics. The best selected algorithms are $A1:R(Z,K_{dp})$ and $A12:R(Z_{dr},K_{dp})$ (among the bi-variable); $B2:R(Z_h,Z_{dr},K_{dp})$ and $B3:R(A_h,Z_{dr},K_{dp})$ (among the tri-variable). Tri-variable algorithms outperform bi-variable algorithms. Validation with observation data (Xport measurements and rain gauge network) showed that the algorithm $B3:R(A_h,Z_{dr},K_{dp})$ performs better than $B2:R(Z_h,Z_{dr},K_{dp})$. Full article

Introduction: Lassa fever disease (LFD) is an acute viral haemorrhagic fever caused by Lassa virus. It is a disease of public health importance in West Africa and a global health threat. It is endemic in some West African countries like Benin, Ghana, Guinea, Liberia, Mali, Sierra Leone, and Nigeria, where an estimated 300,000 to 500,000 cases occur every year with an estimated 5000 annual deaths. Persons living in rural areas and health care workers are at greatest risk. Public awareness and knowledge of the LFD and its risk factors are some of the important factors that determine disease transmission and success of preventive/control efforts. This study was therefore conducted to assess LFD-related awareness and knowledge in Gangara, a rural agrarian community in Giwa Local Government Area of Kuduna State, NorthWest Nigeria. Methods: A cross-sectional, community based descriptive study conducted in Gangara community. An interviewer- administered questionnaire was used to collect data from 556 adult respondents, selected using systematic random sampling technique. Data was analyzed using SPSS (version 20). Results: A majority of the respondents were females (52.9%) with a mean age of 37.0 ± 15.2. The level of awareness of LFD was high (66.7%) among respondents and there was a statistically significant association between awareness of LFD and not having any form of education (P < 0.00). However, most of the respondents (79.0%) have poor knowledge of LFD. Knowledge of risk factors for LFD was also poor with 59.4% not knowing that drying grains and foodstuffs on the ground is a risk factor for LFD. Conclusions: Awareness of the disease was quite high but knowledge of the disease and its risk factors was poor. For effective prevention of future outbreaks, the community needs to be properly educated on LFD and its risk factors. Full article

The concept of Environmental Migration has been broadly discussed by the international scientific community. Especially developing countries will have to develop strategies to cope with a rising number of people migrating at national and international levels due to climatic changes and environmental degradation. This paper will critically analyze the term Environmental Migration and sets it in relation to a case study conducted in northwest Benin in August/October of 2013 with Bialaba, analyzing their temporary migration pattern to Nigeria. The aim is to reveal current discussions on the term “Environmental Migration”/“Environmental Migrant” and to discuss its conceptual limits. The qualitative study in this working paper was conducted in the form of 36 interviews with farmers in the Dassari watershed North of Benin and surrounding villages as well as with stakeholders of the local government and NGOs active in the research area. Research results are presented in the following paper to clarify migration motives for the Bialaba of northwest Benin towards Nigeria aiming to stimulate discussions on the topic and to promote new research pathways. Full article