Survival of faecal coliforms in four different types of sludge-amended soils in Botswana

This study aimed at identifying the factors that affected the survival of faecal coliforms as measured by E. coli in four types of soils in Botswana which were amended with sewage sludge. Physico-chemical and biochemical properties and coliform population in the different soils, sludge, and soil/sludge mixtures were determined after sampling, on composing the soil/sludge mixtures, and 90 days after composing. Coliform population in the different soil/sludge mixtures decreased by about 90% after 90 days. The age of the sludge used and the rate at which it was applied to the soils initially determined the population of E. coli in each soil/sludge mixture, but after 90 days, differences inherent in the different soil types were the main determinants of the E. coli population. Percentage reduction of coliforms in Type 1 sludge mixtures were lower (38%) than in Type 2 sludge mixtures (57%). Up to 79.8% of the reduction observed in E. coli population in the Barolong luvisol-sludge mixtures after 90 days was caused by reduction in pH and moisture content, while 72.6%, 84.5% and 55.1% of the reduction in E. coli population in Tuli luvisol-, arenosol- and vertisol-sludge mixtures, respectively, was accounted for by the reduction in moisture content and Olsen P concentration. Coliform survival rates varied with soil types being 12%, 6.4%, 5.3% and 5.8% for the vertisol, arenosol, Barolong luvisol and Tuli luvisol, respectively. A minimum period of 90 days should be allowed between when sludge is applied to similar soils and when seeds are sown. The exact period should, however, be determined by the properties of the soil with fine-textured soils requiring a longer period than coarse-textured soils.     

Suitability of terrestrial laser scanning for studying surface roughness effects on concentrated flow erosion processes in rangelands

Surface roughness is thought to affect concentrated flow erosion – a major mechanism of soil loss on disturbed rangelands. However, quantifying surface roughness in the field at appropriately fine spatial scales is laborious and the scale at which to conduct meaningful roughness measurements is difficult to discern. Rapid, objective, and repeatable field methods are therefore needed to accurately measure surface roughness across a range of spatial scales to advance our understanding and modeling of concentrated flow erosion processes. Surface roughness can be derived from surface topography mapped at the sub-cm level using a field-portable terrestrial laser scanner (TLS). To test the suitability of terrestrial laser scanning for studying surface roughness effects on erosion processes in rangelands, we used concentrated flow simulation techniques at 8.5 m² plots that were randomly placed at rangeland sites in southeastern Oregon and southwestern Idaho, USA. Local surface roughness (locRMSH) was calculated as the standard deviation of TLS mapped surface heights within moving windows varying in size from 30 × 30 to 90 × 90 mm. The mean locRMSH of the eroded area and entire plot were negatively correlated (r² > 0.71, RMSE < 95.97 g min^− 1, and r² > 0.74, RMSE < 90.07 g min^− 1, respectively) with concentrated flow erosion. The strength of the locRMSH–erosion relationship and regression model parameters were affected by the moving window size, emphasizing the scale dependence of the locRMSH–erosion relationship. Adjusting locRMSH for slope effects decreased the strength of the locRMSH–erosion relationship from r² < 0.83 to < 0.26. Our results indicate that TLS is a useful tool to enhance our current understanding of the effect of surface roughness on overland flow erosion processes and advance hydrologic and erosion model parameter development. Further research is needed to evaluate the locRMSH – concentrated flow erosion relationship over a wider range of soil properties, surface conditions, and spatial extents.     

Understanding Ebola virus and other zoonotic transmission risks through human–bat contacts: Exploratory study on knowledge,attitudes and practices in Southern Cameroon

The ecology of Ebola virus (EBV) remains largely unknown, but the previous detection of viral RNA and anti‐EBV antibodies in African bats suggests that they might play a role in the EBV reservoir. Moreover, African bats also carry other potentially zoonotic agents such as Henipah‐like viruses, coronaviruses and lyssaviruses. Today only little information is available on interactions between humans and bats. The objective of our exploratory study was to describe the extent and modes of contacts between humans and bats in southern Cameroon, considered as an area at risk for future EBV outbreaks. The survey was conducted in 11 villages of four distinct rural areas in southern Cameroon. A total of 135 respondents were interviewed using semi‐structured questionnaires, between February and May 2017. The study showed that direct contacts between bats and humans are relatively common. Bat bushmeat appeared to be an occasional meat resource; 40% of respondents consume bats with a median annual consumption of three, and 28% of respondents hunt them. About 22% of the respondents reported children catching bats. Indirect contact also appeared to be common; 55% of hunters use caves as shelters and 67% of interviewees eat fruits previously chewed by bats. Bat consumption varied significantly between regions (from 0% to 87%) and between pygmies and bantus in the extreme south‐east of Cameroon. The study revealed considerable diversity in practices among interviewees, most of them being subsistence cultivators and relying on self‐hunted bushmeat. Geographical diversity of contacts and perceptions regarding bats in Cameroon emphasizes the need to adjust zoonotic pathogen surveillance and education campaigns to the specificities of the communities and their context of interaction with wildlife.     

A spectral index to monitor the head-emergence of wheat in semi-arid conditions

Harvesting wheat (Triticium aestivum L.) for forage or leaving it for grain is the main decision uncertainty growers face in semi-arid regions during mid-season. To facilitate decision-making, a decision support system (DSS) has recently been proposed that requires information about crop water and nutritional status during spike emergence. Though remote sensing has been used to provide site-specific crop status information, a spectral vegetation index is needed to ensure that the information has been acquired during spike emergence. The objective of this study was to propose a spectral index sensitive to spike emergence and validate its suitability across different commercial farm fields by using ground spectral measurements and multispectral satellite imagery. To develop the index, controlled experiments with commonly grown wheat varieties were conducted during the 2004/2005 and 2005/2006 growing season in the agricultural area of the northern Negev desert of Israel. The experiments showed that spike emergence correlated most strongly (r = 0.7, p < 0.05) with spectral changes near the 1.2 μm water absorption feature in contrast to the band at 1.1 μm which appeared to be only weakly correlated. Thus, the spike emergence sensitive band at 1.2 μm has been combined with the insensitive band at 1.1 μm as reference to form the ratio-based normalized heading index (NHI). Experimental data were then used to establish an index threshold that helps separate data acquired before and after spike emergence. The proposed NHI was able to identify spike emergence with a classification accuracy varying between 53 and 83%. Accuracy was influenced by season, and whether narrow or broad spectral bands were used. Validation of the index in commercial farm fields in Israel and the United States showed that the classification accuracy was similar for ground spectral measurements and the advanced land imager (ALI) satellite imagery. These results suggest that the NHI is suited for identifying the onset of heading throughout wheat-growing areas without the need for characterizing seasonal trends.     

Chimpanzee reservoirs of pandemic and nonpandemic HIV-1

Human immunodeficiency virus type 1 (HIV-1), the cause of human acquired immunodeficiency syndrome (AIDS), is a zoonotic infection of staggering proportions and social impact. Yet uncertainty persists regarding its natural reservoir. The virus most closely related to HIV-1 is a simian immunodeficiency virus (SIV) thus far identified only in captive members of the chimpanzee subspecies Pan troglodytes troglodytes. Here we report the detection of SIVcpz antibodies and nucleic acids in fecal samples from wild-living P. t. troglodytes apes in southern Cameroon, where prevalence rates in some communities reached 29 to 35%. By sequence analysis of endemic SIVcpz strains, we could trace the origins of pandemic (group M) and nonpandemic (group N) HIV-1 to distinct, geographically isolated chimpanzee communities. These findings establish P. t. troglodytes as a natural reservoir of HIV-1.     

Early season remote sensing of wheat nitrogen status using a green scanning laser

In-season, spatially variable nitrogen (N) fertilizer applications in agricultural systems can help to maximize crop N use efficiency and minimize N losses via hydrological leaching, runoff, and atmospheric volatilization. N fertilizer management often relies upon measurements of crop spectral reflectance using ground-based optical on-the-go sensors or hand-held chlorophyll meters. However, soil background reflectance can confound on-the-go sensing, especially during early crop growth stages, and hand-held chlorophyll meters are impractical for spatially explicit mapping at the field scale. Scanning laser technology is available that measures the intensity of the reflected laser light plus height information within a mm-scale ground instantaneous field of view at a very high sampling rate (up to 50,000 points s⁻¹ in this study). We examined the ability to quantify foliar N status of spring wheat (Triticum aestivum L.) using a green (532 nm) terrestrial laser scanner during an early stem extension growth stage (Zadoks growth stage 3.2). Laser data were processed by (1) removing soil background returns based on laser-determined height information, (2) standardizing green laser intensity based on white-reference panel readings, and (3) filtering noisy laser returns from leaf edges based on a laser return intensity threshold value. The return intensity of the reflected green laser light more accurately (r² = 0.68, RMSE = 0.30 μg g⁻¹) predicted foliar N concentration than conventional chlorophyll meter readings (r² = 0.36, RMSE = 0.41 μg g⁻¹) and spectral indices measured by a ground optical on-the-go sensor (r² < 0.41, RMSE > 0.39 μg g⁻¹). The results indicate that laser scanners are useful for measuring the N status of wheat during early growth stages, and provide justification for incorporating laser scanner based measurements into developing spatially-explicit estimates of foliar N during this critical growth period. Further research is needed to evaluate the operational practicality of a green scanning laser from a moving platform.     

Mapping wheat nitrogen uptake from RapidEye vegetation indices

Mapping wheat nitrogen (N) uptake at 5 m spatial resolution could provide growers with new insights regarding nitrogen-use efficiency at the field scale. This study explored the use of spectral information from high resolution (5 × 5 m) RapidEye satellite data at peak leaf area index (LAI) to estimate end-of-season cumulative N uptake of wheat (Triticum spp.) in a heterogeneous, rainfed system. The primary objectives were to evaluate the usefulness of simple, widely used vegetation indices (VIs) from RapidEye as a tool to map crop N uptake over three growing seasons, farms and growing conditions, and to examine the usefulness of remotely sensed N uptake maps for precision agriculture applications. Data on harvested wheat N was collected at twelve plots over three seasons at four farms in the Palouse region of Northern Idaho and Eastern Washington. Seventeen commonly used spectral VIs were computed for images collected during ‘peak greenness’ (maximum LAI) to determine which VIs would be most appropriate for estimating wheat N uptake at harvest. The normalized difference red-edge index was the top performing VI, explaining 81 % of the variance in wheat N uptake with a regression slope of 1.06 and RMSE of 15.94 kg/ha. Model performance was strong across all farms over all three seasons regardless of crop variety, allowing the creation of high accuracy wheat N uptake maps. In conclusion, for this particular agro-ecosystem, mid-season VIs that incorporate the use of the NIR and red-edge bands are generally better predictors of end-of-season crop N uptake than VIs that do not include these bands, thereby further enabling their use in precision agriculture applications.     

Internal Parasites and Haematological Values in Cattle Slaughtered in Buea Subdivision of Cameroon

Tropical Animal Health and Production -