Developed nations intervened in conservation policy across Africa during the 20th century to address needs to protect species and biodiversity that were based on their own perceptions and priorities. In the 21st century, conservationists in Africa have revised these perceptions and begun the process of identifying conservation priorities from an African perspective and in consideration of Africans' priorities. Although foreign conservation interveners struggled to identify mechanisms to which local people would respond, African conservationists are now demonstrating how to integrate the continent's unique socioeconomic circumstances into efforts to protect biodiversity. In Africa effective conservation policy must include the generation of wealth, reduction of disease and hunger, and support of traditional land-use practices.

This study assessed the influence of hydrological variables on macrophytes in a Black Water River ecosystem of Enyong River in Itu and Ibiono Local Government Areas of Akwa Ibom and Cross Rivers States, Nigeria. Four vegetation plots were chosen and in each of the plots, four belt transect were laid. In each transect, macrophyte were systematically sampled in four 10 m × 10 m quadrat at regular intervals. Macrophytes were identified to species level and their frequency and density determined. Water samples were obtained in each quadrat where the macrophytes were sampled and analyzed for their physicochemical properties using standardized methods. Altogether, 10 macrophyte species were encountered. Vossia cuspidata had the highest density (100.00±8.00 st/ha) and frequency values (100 %). Sacciolepis africana had the least density of 7.10±0.45 st/ha while Ludwigia octovalvis, Persicaria senegalensis, andSacciolepis africana had the least frequency of 25 %, respectively. The pH of the water was strongly acidic (5.54±0.03), electrical conductivity was low (20.00±5.77 µs/cm), temperature (29.00±1.10 ºC), Dissolved Oxygen (DO) (9.20±0.12 mg/l) and turbidity (7.10±0.06 NTU) values were high while Biological Oxygen Demand (BOD) (2.00±0.29 mg/l) Total Dissolved Solids (TDS) (10.00±0.29 mg/l) and Total Suspended Solids (TSS) were low (5.00±1.15 mg/l). Water Nutrients followed this decreasing order; chloride (3.55±0.02 mg/l) > nitrate (2.45±0.03 mg/l) > sulphate (2.02±0.06 mg/l) > phosphate (0.08±0.01 mg/l) and sulphide (0.03±0.02 mg/l). Heavy metals also followed this descending order; Pb (0.50±0.03 mg/l) > Zn (0.07±0.02 mg/l) > Cu (0.03±0.02 mg/l). Canonical Correspondence Analysis delineated 11 hydrological variables (temperature, pH, sulphate, turbidity, phosphate, BOD, nitrate, DO, TDS, sulphide and TSS) which exerted great influence on macrophyte distribution. V. cuspidata had affinity to pH and temperature, Sacciolepis africana had affinity to turbidity and BOD, Ludwigia octovalvis and Nymphaea lotus had affinity to sulphate and chloride, respectively, while Ipomoea aquatica and Alternanthera sessils had affinity to phosphate. On the other hand, Persicaria senegalensis, Salvinia molesta, Azolla pinnata and Ceratophyllum demersum had affinities to sulphide, DO, TSS and TDS, respectively. Since hydrological variables regulate macrophyte diversity and distribution, this study calls for consistent, monitoring and management of this ecosystem against future environmental changes. Keywords: Aquatic plants, Black water, Canonical Correspondence Analysis, Ordination

Whereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and January 15, 2021, a total of 8864 human SARS-CoV-2 complete genome sequences processed by gender, across 6 continents (88 countries) of the world, Antarctica exempt, were analyzed. We hypothesized that data speak for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate the emergence of inter- and intra- SARS-CoV-2 sub-strains transmission and sustain an increase in sub-strains within the various continents, with nucleotide mutations dynamically varying between individuals in close association with the virus as it adapts to its host/environment. Interestingly, some viral sub-strain patterns progressively transformed into new sub-strain clusters indicating varying amino acid, and strong nucleotide association derived from same lineage. A novel cognitive approach to knowledge mining helped the discovery of transmission routes and seamless contact tracing protocol. Our classification results were better than state-of-the-art methods, indicating a more robust system for predicting emerging or new viral sub-strain(s). The results therefore offer explanations for the growing concerns about the virus and its next wave(s). A future direction of this work is a defuzzification of confusable pattern clusters for precise intra-country SARS-CoV-2 sub-strains analytics.

BackgroundThe increased number of accessible genomes has prompted large-scale comparative studies for decerning evolutionary knowledge of infectious diseases, but challenges such as non-availability of close reference sequence(s), incompletely assembled or large number of genomes, preclude real time multiple sequence alignment and sub-strain(s) discovery. This paper introduces a cooperatively inspired open-source framework, for intelligent mining of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genomes. We situate this study within the African context, to drive advancement on state-of-the-art, towards intelligent infectious disease characterization and prediction. The outcome is an enriched Knowledge Base, sufficient to provide deep understanding of the viral sub-strains’ identification problem. We also open investigation by gender, which to the best of our knowledge has been ignored in related research. Data for the study came from the Global Initiative on Sharing All Influenza Data database (https://gisaid.org) and processed for precise discovery of viral sub-strains transmission between and within African countries. To localize the transmission route(s) of each isolate excavated and provide appropriate links to similar isolate strain(s), a cognitive solution was imposed on the genome expression patterns discovered by unsupervised self-organizing map (SOM) component planes visualization. The Freidman-Nemenyi’s test was finally performed to validate our claim.ResultsEvidence of inter- and intra-genome diversity was noticed. While some isolates (or genomes) clustered differently, implying different evolutionary source (or high-diversity), others clustered closely together, indicating similar evolutionary source (or less-diversity). SOM component planes analysis revealed multiple sub-strains patterns, strongly suggesting local or intra-community and country to country transmissions. Cognitive maps of both male and female isolates revealed multiple transmission routes. Statistical results indicate significant difference between the various isolate groups at the 0.05 level of significance.ConclusionThe proposed framework offers explanations to SARS-CoV-2 diversity and provides real time identification to disease transmission routes, as well as rapid decision support for facilitating inter- and intra-country contact tracing of infected case(s). Intermediate data produced in this paper are helpful to enrich the genome datasets for intelligent characterization and prediction of COVID-19 and related pandemics, as well as the construction of intelligent device for accurate infectious disease monitoring.