Population structure of the widespread species, Anogeissus leiocarpa (DC.) Guill. & Perr. across the climatic gradient in West Africa semi-arid area

AbstractIn the climate change context, widely distributed plant species can serve as relevant barometers of ecosystems' sensitivity or resilience to disturbances. This study aimed at assessing the population structure and individual morphological traits of Anogeissus leiocarpa, a widespread tree species, across a broad strip of land, from the north to the south of Burkina Faso. We compared stands in four phytogeographical zones in order to analyze morphological variations in trees and recruits density, individual size and their spatial structure. Our results showed significant increase of tree density from the Sahel (77.1 trees/ha) to the South-Sudanian (166 trees/ha) while diameter, height and basal area had an opposite trend. No recruits were found in the Sahel stands, while their density increased from the Sub-Sahel (5.17 individuals/ha) to the South-Sudanian (6.46 individuals/ha). Tree diameters revealed positive asymmetric distributions in the Sudanian and Sub-Sahel whereas the Sahel stands showed a symmetric distribution. Height structure of saplings revealed “J reverse” shape in Sudanian stands while Sub-Sahelian ones exhibited Gaussian shape. Height–diameter relationships revealed thin trees towards the south-Sudanian. The spatial structure of trees indicated random distributions in all zones whereas recruits presented aggregative distribution trend in the Sudanian zones. A. leiocarpa's trees have a good ability to support broad climatic fluctuations but the populations' rejuvenation is unpredictable in the extreme harsh conditions. The species is fairly resilient to anthropogenic disturbances in Sub-Sahel and Sudanian zones. However, managing issues should pay attention to the species communities by considering its demographic behavior in the health state appreciation of ecosystems

Modeling the effects of Prophylactic behaviors on the spread of SARS-CoV-2 in West Africa

Various general and individual measures have been implemented to limit the spread of SARS-CoV-2 since its emergence in China. Several phenomenological and mechanistic models have been developed to inform and guide health policy. Many of these models ignore opinions about certain control measures, although various opinions and attitudes can influence individual actions. To account for the effects of prophylactic opinions on disease dynamics and to avoid identifiability problems, we expand the SIR-Opinion model of Tyson et al. (2020) to take into account the partial detection of infected individuals in order to provide robust modeling of COVID-19 as well as degrees of adherence to prophylactic treatments, taking into account a hybrid modeling technique using Richard's model and the logistic model. Applying the approach to COVID-19 data from West Africa demonstrates that the more people with a strong prophylactic opinion, the smaller the final COVID-19 pandemic size. The influence of individuals on each other and from the media significantly influences the susceptible population and, thus, the dynamics of the disease. Thus, when considering the opinion of susceptible individuals to the disease, the view of the population at baseline influences its dynamics. The results are expected to inform public policy in the context of emerging and re-emerging infectious diseases

Identification of socio-economic characteristics and farmers’ practices affecting rice (Oryza spp.) yields in Benin (West Africa)

Rice (Oryza spp.) is one of the major staple foods in Benin. Benin has increased rice production through the expansion of cultivation area rather than increasing rice yields. To better understand the factors affecting rice yields, a thorough understanding of the current rice production system characteristics and constraints is required. The present study identifies socio-economic characteristics and farmers’ practices affecting rice yields and suggests improved cultivation practices in the sector. Data were collected through semi-structured interviews, including socio-economic characteristics and rice cultivation practices from 230 randomly selected rice producers in North and Central Benin. Descriptive statistics and cluster analysis were used to group rice producers into different groups. Findings revealed that the proportion of rice producers having access to credit was low (33.5 %). Out of seventeen variables, only three (lowland rice cultivation, irrigated rice cultivation and total land cultivated area) discriminated best the rice producers in three (03) clusters with distinct characteristics in terms of socio-economics factors and cropping practices affecting rice yields. Most respondents (more than 70 %) did not practice crop rotation or fallow. This, together with low levels of chemical fertiliser applications and type of rice cultivation, explains poor rice production in particular in clusters 1 and 2. Yield enhancement is possible through the combination of lowland and irrigated cultivation performed by farmers in cluster 3 with the highest mean rice yield (3.8 t.ha-1). We suggest tackling the specific characteristics and needs of rice producers would more adequately help to improve rice yields. Interventions to enhance rice yields include training on best rice production practices, provision of input subsidies and access to irrigation tailored to the specific constraints and needs of each rice grower type. Finally, enabling access to credit will improve productivity of rice farmers in Benin

Natural intraspecific trait variation patterns of the wild soursop Annona senegalensis (Annonaceae) along a climatic gradient in Benin, West Africa

Background and aims – Geographic patterns of phenotypic variability can inform understanding of the resilience potential of plant species to environmental hazards such as climate change. Such understanding provides support for conservation and domestication efforts. Here, we investigated natural morphological variation of the individuals, fruits, seeds, and leaves of the tropical shrub Annona senegalensis Pers. along a climatic gradient. Methods – Morphological data were collected on shrubs, fruits, seeds, and leaves of 150 shrubs from five populations in the three climatic zones of Benin. Linear mixed effects models were used to test the variability of the morphological traits of the species and also to estimate the variance components in order to tease apart the importance of each source of variation. The most important morphological descriptors discriminating climatic zones were identified using a stepwise discriminant analysis. Redundancy analysis was then used to determine the relationships between discriminant morphological traits and bioclimatic variables. Key results – Morphological traits of A. senegalensis varied greatly both within and among climatic zones. A substantial part (42%) of the among-climatic zones phenotypic variability in the species was attributable to climate, mainly rainfall and temperature. Morphological traits such as big shrubs, big fruits, and high number of seeds per fruit were associated with high mean annual rainfall and low mean temperature of the warmest quarter. Conclusions – The findings suggest an important zonal adaptation of the species to climate variability. The phenotypic diversity pattern that we highlighted can be useful when designing conservation policies for the species. However, quantitative genetics through common garden or reciprocal transplantation experiments related to the species’ populations would enable to explore the heritable part of the observed variability to support effective conservation and domestication efforts

How Far the Mono Transboundary Biosphere Reserve Protects Biodiversity in the Dahomey-Gap Corridor, West Africa?

Mono Transboundary Biosphere Reserve (MTBR) is rich in biodiversity associated with different multi-functional ecosystems in the Dahomey-Gap corridor in the southern border between Benin and Togo. The reserve has been facing many anthropogenic pressures since few years including the uncontrolled exploitation of forest resources, and fragmentation of habitats and permanent search for arable land. Thus, it becomes important to develop prospective analysis approaches in order to provide specific insights for a balanced biodiversity. This study aims to provide scientific evidence to better understand and project future changes in LULC in the MTBR at different spatial and temporal scales. Changes in LULC were used to map the MTBR in 1986, 2000, and 2015 and to predict the LULC in the future up to 2070 using Markovian chain analysis. During 1986–2000, urban agglomeration/bare soil (8.79 ha/year) increased, whereas the natural vegetation cover increased during the period 2000–2015, particularly mangroves (9.81 ha/year). Assuming the dynamic observed, the mangroves will increase by 2070 (6% of its cover). However, an important increase is also expected for farmland (13% of its cover). It is, therefore, important to strengthen the actions and strategies around and within the MTBR for sustainable management of biological resources

Traditional knowledge and cultural importance of Borassus aethiopum Mart. in Benin: interacting effects of socio-demographic attributes and multi-scale abundance

ResearchBackground: Eliciting factors affecting distribution of traditional knowledge (TK) and cultural importance of plant resources is central in ethnobiology. Socio-demographic attributes and ecological apparency hypothesis (EAH) have been widely documented as drivers of TK distribution, but their synergistic effect is poorly documented. Here, we focused on Borassus aethiopum, a socio-economic important agroforestry palm in Africa, analyzing relationships between the number of use-reports and cultural importance on one hand, and informant socio-demographic attributes (age category and gender) on the other hand, considering the EAH at multi-scale contexts. Our hypothesis is that effects of socio-demographic attributes on use-reports and cultural importance are shaped by both local (village level) and regional (chorological region level) apparency of study species. We expected so because distribution of knowledge on a resource in a community correlates to the versatility in the resource utilization but also connections among communities within a region. Methods: Nine hundred ninety-two face-to-face individual semi-structured interviews were conducted in six villages of low versus high local abundance of B. aethiopum spanning three chorological regions (humid, sub-humid and semiarid) also underlying a gradient of increasing distribution and abundance of B. aethiopum. Number of use-reports and score of importance of uses of B. aethiopum were recorded in six use-categories including medicine, food, handcraft, construction, firewood, and ceremonies and rituals. Data were analyzed using Poisson and ordered logistic modelsinfo:eu-repo/semantics/publishedVersio

Strengthening capacity building in data analysis in West African Universities and research institutions: A three-year experience of the Master Programme in Biostatistics at the University of Abomey-Calavi, Benin

Scientific research plays a key role in development, especially in economic growth of countries. Scientific innovations, the main outcome of scientific research, require the use of modern statistical and mathematical methods in research works. In Africa, especially sub-Saharan Africa, Statistics is underutilized and some situations misused in biological researches. The master programme in Statistics, major Biostatistics at the University of Abomey-Calavi has been created and implemented by the Laboratory of Biomathematics and Forest Estimations at the Faculty of Agronomic Sciences in order to fill this gap. This master programme has four semesters and is taught in English with lecturers mainly coming from Benin and Togo, but also some come from United States of America (USA) and Belgium. Analysis of the three-year experience of this programme reveals an increasing trend of the number of students involved with a total of 44 students coming from 12 African countries. Defense of the first batch of students in this master programme (24-29 February, 2016) targeted some modern statistical and mathematical methods including linear and non-linear mixed effects models, matrix projection models, ordination methods, generalized linear models, survival analyses and efficiency analyses with applications in biology. The current challenges linked to this master programme can be lessened through a partnership with the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM), universities and research institutions in other countries in West Africa (Ghana, Nigeria), Eastern Africa (Uganda, Kenya) and Southern African (South Africa) to share and improve curricula in Biostatistics training

A Hybrid Modeling Technique of Epidemic Outbreaks with Application to COVID-19 Dynamics in West Africa

The widely used logistic model for epidemic case reporting data may be either restrictive or unrealistic in presence of containment measures when implemented after an epidemic outbreak. For flexibility in epidemic case reporting data modeling, we combined an exponential growth curve for the early epidemic phase with a flexible growth curve to account for the potential change in growth pattern after implementation of containment measures. We also fitted logistic regression models to recoveries and deaths from the confirmed positive cases. In addition, the growth curves were integrated into a SIQR (Susceptible, Infective, Quarantined, Recovered) model framework to provide an overview on the modeled epidemic wave. We focused on the estimation of: (1) the delay between the appearance of the first infectious case in the population and the outbreak (“epidemic latency period”); (2) the duration of the exponential growth phase; (3) the basic and the time-varying reproduction numbers; and (4) the peaks (time and size) in confirmed positive cases, active cases and new infections. The application of this approach to COVID-19 data from West Africa allowed discussion on the effectiveness of some containment measures implemented across the region

On the use of growth models to understand epidemic outbreaks with application to COVID-19 data.

The initial phase dynamics of an epidemic without containment measures is commonly well modelled using exponential growth models. However, in the presence of containment measures, the exponential model becomes less appropriate. Under the implementation of an isolation measure for detected infectives, we propose to model epidemic dynamics by fitting a flexible growth model curve to reported positive cases, and to infer the overall epidemic dynamics by introducing information on the detection/testing effort and recovery and death rates. The resulting modelling approach is close to the Susceptible-Infectious-Quarantined-Recovered model framework. We focused on predicting the peaks (time and size) in positive cases, active cases and new infections. We applied the approach to data from the COVID-19 outbreak in Italy. Fits on limited data before the observed peaks illustrate the ability of the flexible growth model to approach the estimates from the whole data