Phenology of Woody Species Along the Climatic Gradient in West Tropical Africa

International audienc

Computation of haplotypes on SNPs subsets: advantage of the "global method"

BACKGROUND: Genetic association studies aim at finding correlations between a disease state and genetic variations such as SNPs or combinations of SNPs, termed haplotypes. Some haplotypes have a particular biological meaning such as the ones derived from SNPs located in the promoters, or the ones derived from non synonymous SNPs. All these haplotypes are "subhaplotypes" because they refer only to a part of the SNPs found in the gene. Until now, subhaplotypes were directly computed from the very SNPs chosen to constitute them, without taking into account the rest of the information corresponding to the other SNPs located in the gene. In the present work, we describe an alternative approach, called the "global method", which takes into account all the SNPs known in the region and compare the efficacy of the two "direct" and "global" methods. RESULTS: We used empirical haplotypes data sets from the GH1 promoter and the APOE gene, and 10 simulated datasets, and randomly introduced in them missing information (from 0% up to 20%) to compare the 2 methods. For each method, we used the PHASE haplotyping software since it was described to be the best. We showed that the use of the "global method" for subhaplotyping leads always to a better error rate than the classical direct haplotyping. The advantage provided by this alternative method increases with the percentage of missing genotyping data (diminution of the average error rate from 25% to less than 10%). We applied the global method software on the GRIV cohort for AIDS genetic associations and some associations previously identified through direct subhaplotyping were found to be erroneous. CONCLUSION: The global method for subhaplotyping can reduce, sometimes dramatically, the error rate on patient resolutions and haplotypes frequencies. One should thus use this method in order to minimise the risk of a false interpretation in genetic studies involving subhaplotypes. In practice the global method is always more efficient than the direct method, but a combination method taking into account the level of missing information in each subject appears to be even more interesting when the level of missing information becomes larger (>10%)

Patterns of healthcare seeking among people reporting chronic conditions in rural sub-Saharan Africa: findings from a population-based study in Burkina Faso.

OBJECTIVE: Non-communicable diseases are rapidly becoming one of the leading causes of morbidity and mortality in sub-Saharan Africa. Yet, little is known about patterns of healthcare seeking among people with chronic conditions in these settings. We aimed to explore determinants of healthcare seeking among people who reported at least one chronic condition in rural Burkina Faso. METHODS: Data were drawn from a cross-sectional population-based survey conducted across 24 districts on 52 562 individuals from March to June 2017. We used multinomial logistic regression to assess factors associated with seeking care at a formal provider (facility-based care) or at an informal provider (home and traditional treatment) compared to no care. RESULTS: 1124 individuals (2% of all respondents) reported at least one chronic condition. Among those, 22.8% reported formal care use, 10.6% informal care use, and 66.6% no care. The presence of other household members reporting a chronic condition (RRR = 0.57, 95%-CI [0.39, 0.82]) was negatively associated with seeking formal care. Wealthier households (RRR = 2.14, 95%-CI [1.26, 3.64]), perceived illness severity (RRR = 3.23, 95%-CI [2.22, 4.70]) and suffering from major chronic conditions (RRR = 1.54, 95%-CI [1.13, 2.11]) were positively associated with seeking formal care. CONCLUSION: Only a minority of individuals with chronic conditions sought formal care, with important differences due to socio-economic status. Policies and interventions aimed at increasing the availability and affordability of services for early detection and management in peripheral settings should be prioritised

Desvendando padrões estruturais de fragmentos florestais na Amazônia Oriental

Natural fragments are an important source of richness for the management and conservation of a local flora. The objective of this study was to evaluate the effect of fragmentation on the structure and composition of the plant communities of forest fragments (FF) in Alter do Chão, eastern Brazilian Amazonia. The study sample consisted of 25 FF and nine continuous forest (CF) sites. We compared plant density and species richness between site categories by t-tests, analyzed the differences in composition by cluster analysis, and assessed the effect of fragment size and distance to CF on the basal area and diameter of FF assemblages by linear regression. Individual trees and shrubs with DBH ≥1.27 cm were measured in 2x250 m plots. 17,078 individuals were recorded - 75.32% in FF and 24.68% in CF, comprising 475 species, 216 genera and 64 families. Myrtaceae and Fabaceae were the most abundant families in both FF and CF. Average species richness in FF and CF was statistically different. The 20 species with the highest importance values were similar in FF and CF. The average plant diameter was similar in FF and CF, suggesting that both are "mature" forests composed of thin individuals. Average diameter and total basal area showed a negative relationship with distance to CF and fragment area, respectively. Similarity analysis revealed two groups, one composed exclusively of portions of fragmented forest. Fragments and continuous forest differed in species composition, but were similar in structure. Diameter distribution in fragments was similar to that of primary forests.Fragmentos naturais constituem importante fonte de recursos para o manejo e conservação da flora local. Este trabalho avaliou o efeito da fragmentação sobre a estrutura e a composição das comunidades de plantas de fragmentos florestais (FF), em Alter do Chão, na Amazônia oriental brasileira. Foram amostrados 25 sítios em FF e nove em floresta contínua (CF). Analisamos a diferença na densidade de plantas e na riqueza de espécies entre FF e CF por teste-t, e na composição por análise de agrupamento. Utilizou-se regressão linear para avaliar o efeito do tamanho dos fragmentos e distância à CF sobre a área basal e diâmetro. Os indivíduos com DAP ≥1,27 cm foram medidos em parcelas de 2x250 m. Foram registrados 17.078 indivíduos, 75,32% nos FF e 24,68% na CF, distribuídos em 475 espécies, 216 gêneros e 64 famílias. As famílias Myrtaceae e Fabaceae foram as mais abundantes em ambos FF e CF. A riqueza média diferiu significativamente entre FF e CF. As 20 espécies com maior valor de importância foram semelhantes nos FF e CF. O diâmetro médio nos FF e CF foi semelhante, sugerindo tratar-se em ambos casos de florestas "maduras" compostas por indivíduos finos. O diâmetro médio e a área basal total mostraram relação negativa com a distância à CF e área dos fragmentos, respectivamente. A análise de similaridade revelou dois grupos, um deles composto exclusivamente por fragmentos. Composicionalmente, os fragmentos diferiram da floresta contínua, sendo estruturalmente semelhantes entre si, evidenciando distribuição diamétrica semelhante à das florestas primárias

Environmental and sanitary conditions of guanabara bay, Rio de Janeiro

Guanabara Bay is the second largest bay in the coast of Brazil, with an area of 384 km2. In its surroundings live circa 16 million inhabitants, out of which 6 million live in Rio de Janeiro city, one of the largest cities of the country, and the host of the 2016 Olympic Games. Anthropogenic interference in Guanabara Bay area started early in the XVI century, but environmental impacts escalated from 1930, when this region underwent an industrialization process. Herein we present an overview of the current environmental and sanitary conditions of Guanabara Bay, a consequence of all these decades of impacts. We will focus on microbial communities, how they may affect higher trophic levels of the aquatic community and also human health. The anthropogenic impacts in the bay are flagged by heavy eutrophication and by the emergence of pathogenic microorganisms that are either carried by domestic and/or hospital waste (e.g., virus, KPC-producing bacteria, and fecal coliforms), or that proliferate in such conditions (e.g., vibrios). Antibiotic resistance genes are commonly found in metagenomes of Guanabara Bay planktonic microorganisms. Furthermore, eutrophication results in recurrent algal blooms, with signs of a shift toward flagellated, mixotrophic groups, including several potentially harmful species. A recent large-scale fish kill episode, and a long trend decrease in fish stocks also reflects the bay’s degraded water quality. Although pollution of Guanabara Bay is not a recent problem, the hosting of the 2016 Olympic Games propelled the government to launch a series of plans to restore the bay’s water quality. If all plans are fully implemented, the restoration of Guanabara Bay and its shores may be one of the best legacies of the Olympic Games in Rio de Janeiro

Woody aboveground biomass mapping of the brazilian savanna with a multi-sensor and machine learning approach

The tropical savanna in Brazil known as the Cerrado covers circa 23% of the Brazilian territory, but only 3% of this area is protected. High rates of deforestation and degradation in the woodland and forest areas have made the Cerrado the second-largest source of carbon emissions in Brazil. However, data on these emissions are highly uncertain because of the spatial and temporal variability of the aboveground biomass (AGB) in this biome. Remote-sensing data combined with local vegetation inventories provide the means to quantify the AGB at large scales. Here, we quantify the spatial distribution of woody AGB in the Rio Vermelho watershed, located in the centre of the Cerrado, at a high spatial resolution of 30 metres, with a random forest (RF) machine-learning approach. We produced the first high-resolution map of the AGB for a region in the Brazilian Cerrado using a combination of vegetation inventory plots, airborne light detection and ranging (LiDAR) data, and multispectral and radar satellite images (Landsat 8 and ALOS-2/PALSAR-2). A combination of random forest (RF) models and jackknife analyses enabled us to select the best remote-sensing variables to quantify the AGB on a large scale. Overall, the relationship between the ground data from vegetation inventories and remote-sensing variables was strong (R2 = 0.89), with a root-mean-square error (RMSE) of 7.58 Mg ha−1 and a bias of 0.43 Mg ha−1