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Backgrond: The Sahelian zone of Senegal is marked by heatwave events due to temperatures increase especially in 2013 exceeding 45 ° C with an impact on morbidity and mortality rise. In order to document health impacts of recurrent extreme temperatures in this part of the country, a study was carried out combining heatwaves detection, occurrence of climate-sensitive diseases and risk factors for exposure.Methods: To do this, a set of climatic (temperatures) and health (morbidity, mortality) data were collected for April, May and June season from 2009 to 2019. These data were complemented by surveys on exposure risk factors of 1246 households. Statistical methods were used to carry out univariate and bivariate analyzes while cartographic techniques allowed visualization of the main climatic and health indicators.Results: The results show an increase in temperatures compared to seasonal normal for the 1971-2000 reference period with threshold exceedances of the 90th percentiles (42°C) for the maxima and (27°C) the minima and higher temperatures during the months of May and June. From health perspective, it was noted an increase in cases of consultation on health facilities as well as a rise in declared morbidity by households especially in the departments of Kanel (17.7%), Ranérou (16.1 %), Matam (13.7%) and Bakel (13.7%). The heatwaves of May 2013 were also associated with cases of death with a reported mortality (observed by medical staff) of 12.4% unevenly distributed according to the departments with a higher number of deaths in Matam (25, 2%) and in Bakel (23.5%) than in Podor (8.4%) and Kanel (0.8%). The morbidity and mortality distribution according to gender shows that women (57%) were more affected than men (43%). These health risks have been associated with a number of factors including age, access to drinkable water, type of fuel, type of housing and construction materials, existence of fan, an air conditioner, health antecedents, etc.Conclusion: The heatwaves recurrence has led to an upsurge in certain diseases sensitive to rising temperatures, which is increasingly a public health issue in the Sahelian zone of Senegal.

The Sahelian zone of Senegal experienced heat waves in the previous decades, such as 2013, 2016 and 2018 that were characterised by temperatures exceeding 45°C for up to 3 successive days. The health impacts of these heat waves are not yet analysed in Senegal although their negative effects have been shown in many countries. This study analyses the health impacts of observed extreme temperatures in the Sahelian zone of the country, focusing on morbidity and mortality by combining data from station observation, climate model projections, and household survey to investigate heat wave detection, occurrence of climate-sensitive diseases and risk factors for exposure. To do this, a set of climatic (temperatures) and health (morbidity, mortality) data were collected for the months of April, May and June from 2009 to 2019. These data have been completed with 1246 households' surveys on risk factor exposure. Statistical methods were used to carry out univariate and bivariate analyses while cartographic techniques allowed mapping of the main climatic and health indicators. The results show an increase in temperatures compared to seasonal normal for the 1971-2000 reference period with threshold exceedances of the 90th percentiles (42°C) for the maxima and (27°C) the minima and higher temperatures during the months of May and June. From health perspective, it was noted an increase in cases of consultation in health facilities as well as a rise in declared morbidity by households especially in the departments of Kanel (17.7%), Ranérou (16.1 %), Matam (13.7%) and Bakel (13.7%). The heat waves of May 2013 were also associated with cases of death with a reported mortality (observed by medical staff) of 12.4% unequally distributed according to the departments with a higher number of deaths in Matam (25, 2%) and in Bakel (23.5%) than in Podor (8.4%) and Kanel (0.8%). The morbidity and mortality distribution according to gender shows that women (57%) were more affected than men (43%). These health risks have been associated with a number of factors including age, access to drinkable water, type of fuel, type of housing and construction materials, existence of fan and an air conditioner, and health history.The heat wave recurrence has led to a frequency in certain diseases sensitive to rising temperatures, which is increasingly a public health issue in the Sahelian zone of Senegal.

Backgrond: The Sahelian zone of Senegal is marked by heatwave events due to temperatures increase especially in 2013 exceeding 45 ° C with an impact on morbidity and mortality rise. In order to document health impacts of recurrent extreme temperatures in this part of the country, a study was carried out combining heatwaves detection, occurrence of climate-sensitive diseases and risk factors for exposure. Methods To do this, a set of climatic (temperatures) and health (morbidity, mortality) data were collected for April, May and June season from 2009 to 2019. These data were complemented by surveys on exposure risk factors of 1246 households. Statistical methods were used to carry out univariate and bivariate analyzes while cartographic techniques allowed visualization of the main climatic and health indicators. Results The results show an increase in temperatures compared to seasonal normal for the 1971-2000 reference period with threshold exceedances of the 90th percentiles (42°C) for the maxima and (27°C) the minima and higher temperatures during the months of May and June. From health perspective, it was noted an increase in cases of consultation on health facilities as well as a rise in declared morbidity by households especially in the departments of Kanel (17.7%), Ranérou (16.1%), Matam (13.7%) and Bakel (13.7%). The heatwaves of May 2013 were also associated with cases of death with a reported mortality (observed by medical staff) of 12.4% unevenly distributed according to the departments with a higher number of deaths in Matam (25, 2%) and in Bakel (23.5%) than in Podor (8.4%) and Kanel (0.8%). The morbidity and mortality distribution according to gender shows that women (57%) were more affected than men (43%). These health risks have been associated with a number of factors including age, access to drinkable water, type of fuel, type of housing and construction materials, existence of fan, an air conditioner, health antecedents, etc. Conclusion The heatwaves recurrence has led to an upsurge in certain diseases sensitive to rising temperatures, which is increasingly a public health issue in the Sahelian zone of Senegal.

This database contains nine land use / land cover datasets collected in a standardized manner between 2013 and 2020 in seven tropical countries within the framework of the international JECAM initiative: Burkina Faso (Koumbia), Madagascar (Antsirabe), Brazil (Sao Paulo and Tocantins), Senegal (Nioro and Niakhar), Kenya (Muranga), Cambodia (Kandal) and South Africa (Mpumalanga) (cf Study_sites.kml). These quality-controlled datasets are distinguished by ground data collected at field scale by local experts, with precise geographic coordinates, and following a common protocol. This database, which contains 27 074 records (20 257 crop and 6 817 non-crop) is a geographic layer in Shapefile format in a Geographic Coordinates System with Datum WGS84. Field surveys were conducted yearly in each study zone, either around the growing peak of the cropping season, for the sites with a main growing season linked to the rainy season such as Burkina Faso, or seasonally, for the sites with multiple cropping (e.g. Sao Paulo site). The GPS waypoints were gathered following an opportunistic sampling approach along the roads or tracks according to their accessibility, while ensuring the best representativity of the existing cropping systems in place. GPS waypoints were also recorded on different types of non-crop classes (e.g. natural vegetation, settlement areas, water bodies) to allow differentiating crop and non-crop classes. Waypoints were only recorded for homogenous fields/entities of at least 20 x 20 m². To facilitate the location of sampling areas and the remote acquisition of waypoints, field operators were equipped with GPS tablets providing access to a QGIS project with Very High Spatial Resolution (VHSR) images ordered just before the surveys. For each waypoint, a set of attributes, corresponding to the cropping practices (crop type, cropping pattern, management techniques) were recorded (for more informations about data, see data paper being published). These datasets can be used to validate existing cropland and crop types/practices maps in the tropics, but also, to assess the performances and the robustness of classification methods of cropland and crop types/practices in a large range of Southern farming systems.

International audience; Agroforestry plays a pivotal role for Sahelian communities by allowing simultaneous improvement of food security and conservation of natural ecosystems and their biodiversity. However, agroforestry systems (AFSs) are particularly heterogeneous in sub-Saharan Africa due to small to very small fields, a large variety of agricultural practices and a diversity of parkland compositions and configurations. This makes spatial sampling processes very important but problematic in terms of representativeness of the landscape heterogeneity to allow an effective study of Sahelian AFSs. In this paper, we proposed, tested and assessed a methodological approach for landscape sampling, mapping and characterization while considering the different types of spatial heterogeneity in complex landscapes, such as Sahelian AFSs. Several complementary methods were combined on the basis of a priori knowledge of agroforestry landscape functioning using multisource data, remote sensing methods, and statistical and spatial analyses applied to landscape ecology. First, the landscape heterogeneity was stratified and used to design two weighted, stratified sampling plans for field surveys of tree species and land use/land cover types. Then, with multisource satellite images together with collected field data, the agroforestry systems were mapped, with a satisfactory accuracy of 85.12% and a Kappa index of 0.81. Finally, we used landscape metrics and diversity indices derived from AFS mapping and the tree species inventory to analyze the diversity of the studied AFS located in the Senegalese Peanut Basin. The results of the analysis evidenced the compositional, configurational and functional heterogeneity found in the study area. This allowed us to demonstrate the ability of the sampling strategy proposed in this paper to capture the various types of heterogeneity in agricultural landscapes. We also showed by implementing the method that it can be used for (i) tree biodiversity analysis, (ii) mapping and (iii) characterization of a complex AFS in sub-Saharan Africa.

International audience; CONTEXT: Fostering diversity within agricultural systems can substantially contribute to improved food security among smallholder farmers. Agroforestry parklands are diverse agricultural landscapes where trees can provide an array of ecosystem services. Previous studies analyzing the agricultural landscape diversity-food security nexus in agroforestry parklands have only considered tree cover. OBJECTIVE: We propose an original empirical approach that combines the analysis of spatial data on agricultural landscape diversity with agricultural field monitoring and household surveys. These three sources of data were used to scrutinize the direct and indirect contributions of agricultural landscape diversity to food availability and food access. METHODS: Millet yield was used as a proxy for food availability, and household food access was approximated using the Household Food Insecurity Access Scale (HFIAS) indicator. Two contrasted agroforestry parklands of Central Senegal were chosen as case studies. Firstly, we used a Gradient Boosting Machine (GBM) algorithm to disentangle the relative contribution of landscape diversity, biophysical and crop management variables in explaining millet yield variability. Secondly, we investigated the pathways linking agricultural landscape di-versity to HFIAS using a Correlation Network Analysis (CNA). RESULTS AND CONCLUSIONS: The GBM model explained 77% and 84% of millet yield variability for the two parklands, respectively, with landscape diversity variables accounting for 53% and 47% of relative influence. Among the landscape diversity variables, tree species richness and tree density were the most important ones. Millet yield was positively associated with tree density in the Nioro site until a threshold of 5 trees/ha, and with tree species richness in the two sites. The CNA showed that greater tree cover and larger tree patches were moderately correlated with HFIAS. This suggests that tree species with large crown, as it the case for most fruit bearing tree species in the region, are the main species contributing directly to food access. Agricultural land-scape diversity contributed mainly indirectly to household food access through an "agroecological pathway", i.e. by the provision of ecosystem services regulating and supporting crop production. SIGNIFICANCE: Using an integrated landscape approach relying on up-to-date remote sensing data and recent advances in data analysis methods, our study shows that tree species diversity matters as much as the amount of tree cover for the production of food, and it can contribute to improve food security. We bring a more nuanced picture of the contribution of agricultural landscape diversity to food security suggesting that land management policies supporting food security should consider both tree density and tree species diversity to optimize the co -benefits of trees for the different food security dimensions.

Agroforestry is pointed out by the Intergovernmental Panel on Climate Change report as a key option to respond to climate change and land degradation while simultaneously improving global food security ( IPCC, 2019 ). Faidherbia albida parklands are widespread in Sub-Saharan Africa and provide several ecosystem services to populations, notably an increase in crop productivity. While remote sensing has been proven useful for crop yield assessment in smallholder farming system, it has so far ignored the woody component. We propose an original approach combining remote sensing, landscape ecology and statistical modelling to i) improve the accuracy of millet yield prediction in parklands and ii) identify the main drivers of millet yield spatial variation. The parkland of Central Senegal was chosen as a case study. Firstly, we calibrated a remote sensing-based linear model that accounted for vegetation productivity and tree density to predict millet yield. Integrating parkland structure improved the accuracy of yield estimation. The best model based on a combination of Green Difference Vegetation Index and number of trees in the field explained 70% of observed yield variability (relative Root Mean Squared Error (RRMSE) of 28%). The best model based solely on vegetation productivity (no information on parkland structure) explained only 46% of the observed variability (RRMSE = 34%). Secondly we investigated the drivers of the spatial variability in estimated yield using Gradient Boosting Machine algorithm (GBM) and biophysical and management factors derived from geospatial data. The GBM model explained 81% of yield spatial variability. Predominant drivers were soil nutrient availability (i.e. soil total nitrogen and total phosphorous) and woody cover in the surrounding landscape of fields. Our results show that millet yield increases with woody cover in the surrounding landscape of fields up to a woody cover of 35%. These findings have to be strengthened by testing the approach in more diversified and/or denser parklands. Our study illustrates that recent advances in earth observations open up new avenues to improve the monitoring of parkland systems in smallholder context.

In the context of a growing population and impacts of climate changes on agricultural lands and food security, improving crop monitoring of smallholder farming systems is crucial to reach the Sustainable Development Goal (SDG) 2 «Zero hunger». There is an increasing scientific interest in understanding the effects of the biodiversity induced by tree-based agricultural systems on agricultural production and human nutrition. To elucidate the contribution of landscape diversity to agricultural productivity, this study proposes a sampling strategy guided by landscape heterogeneity to account for tree diversity. We propose a simple and reproducible approach based on remote sensing, object-based segmentation and unsupervised classification. The study was conducted in the Senegalese Peanut Basin characterized by a tree-based agricultural system dominated by Faidherbia albida.

Schistosomiasis is the second most significant parasitic disease in children in several African countries. For this purpose, the "Programme National de Lutte contre les Bilharzioses" (PNLB) was developed in partnership with the World Health Organization (WHO) to control this disease in Senegal. However, geographic isolation of Bedik ethnic groups challenged implementation of the key elements of the schistosomiasis program in eastern Senegal, and therefore, a hospital was established in Ninefescha to improve access to health care as well as laboratory support for this population. The program we have implemented from 2008 in partnership with the PNLB/WHO involved campaigns to 1) evaluate schistosomiasis prevalence in children of 53 villages around Ninefescha hospital, 2) perform a mass drug administration following the protocol established by the PNLB in school-aged children, 3) monitor annual prevalence, 4) implement health education campaigns, and 5) oversee the building of latrines. This campaign led to a drop in schistosomiasis prevalence but highlighted that sustainable schistosomiasis control by praziquantel treatment, awareness of the use of latrines, and inhabitants' voluntary commitment to the program are crucial to improve Schistosoma elimination. Moreover, this study revealed that preschool-aged children, for whom praziquantel was not recommended until 2014 in Senegal, constituted a significant reservoir for the parasite.

Une enquete epidemiologique a ete menee au Senegal oriental – district de Kedougou – dans le but d’etablir la prevalence des bilharzioses intestinale et urinaire chez les enfants d’âge scolaire de 6 a 14 ans. Cinquante-trois villages et hameaux sont concernes soit 3324 enfants. Pour l’etude statistique, on procede, dans chaque village, au tirage au sort d’un enfant sur trois dont les selles et les urines sont analysees. La prevalence globale est alors de 47 %. Une campagne de traitement de masse par praziquantel de tous les enfants de 6 a 14 ans, scolarises ou non, a ete initiee en 2008 associee a des reunions d’information et de sensibilisation des villageois. Apres traitement, la prevalence globale est tombee a 6,9 % en 2009 puis a 3,7 % en 2010, montrant ainsi l’efficacite des sensibilisations et des latrines.

The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural censuses are often poorly georeferenced and crop types are difficult to interpret directly from satellite imagery. In this paper, we present a database made of 24 datasets collected in a standardized manner over nine sites within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative; the sites were spread over seven countries of the tropical belt, and the number of data collection years depended on the site (from 1 to 7 years between 2013 and 2020). These quality-controlled datasets are distinguished by in situ data collected at the field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crops and 6817 noncrops, ranging from 748 plots in 2013 (one site visited) to 5515 in 2015 (six sites visited)) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics. They can also be used to assess the performances and robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP (Jolivot et al., 2021). Made available in DSpace on 2022-01-06T12:00:36Z (GMT). No. of bitstreams: 1 Harmonized-in-situ-datasets-for-agricultural-land-use-2021.pdf: 1589665 bytes, checksum: d254577e188593e533093fe816e3fe00 (MD5) Previous issue date: 2021