Low-cost adaptation options to support green growth in agriculture, water resources, and coastal zones

The regional climate as it is now and in the future will put pressure on investments in sub-Saharan Africa in water resource management, fisheries, and other crop and livestock production systems. Changes in oceanic characteristics across the Atlantic Ocean will result in remarkable vulnerability of coastal ecology, littorals, and mangroves in the middle of the twenty-first century and beyond. In line with the countries' objectives of creating a green economy that allows reduced greenhouse gas emissions, improved resource efficiency, and prevention of biodiversity loss, we identify the most pressing needs for adaptation and the best adaptation choices that are also clean and affordable. According to empirical data from the field and customized model simulation designs, the cost of these adaptation measures will likely decrease and benefit sustainable green growth in agriculture, water resource management, and coastal ecosystems, as hydroclimatic hazards such as pluviometric and thermal extremes become more common in West Africa. Most of these adaptation options are local and need to be scaled up and operationalized for sustainable development. Governmental sovereign wealth funds, investments from the private sector, and funding from global climate funds can be used to operationalize these adaptation measures. Effective legislation, knowledge transfer, and pertinent collaborations are necessary for their success

Low-cost adaptation options to support green growth in agriculture, water resources, and coastal zones

The regional climate as it is now and in the future will put pressure on investments in sub-Saharan Africa in water resource management, fisheries, and other crop and livestock production systems. Changes in oceanic characteristics across the Atlantic Ocean will result in remarkable vulnerability of coastal ecology, littorals, and mangroves in the middle of the twenty-first century and beyond. In line with the countries' objectives of creating a green economy that allows reduced greenhouse gas emissions, improved resource efficiency, and prevention of biodiversity loss, we identify the most pressing needs for adaptation and the best adaptation choices that are also clean and affordable. According to empirical data from the field and customized model simulation designs, the cost of these adaptation measures will likely decrease and benefit sustainable green growth in agriculture, water resource management, and coastal ecosystems, as hydroclimatic hazards such as pluviometric and thermal extremes become more common in West Africa. Most of these adaptation options are local and need to be scaled up and operationalized for sustainable development. Governmental sovereign wealth funds, investments from the private sector, and funding from global climate funds can be used to operationalize these adaptation measures. Effective legislation, knowledge transfer, and pertinent collaborations are necessary for their success

Identification of human semiochemicals attractive to the major vectors of onchocerciasis

Background: Entomological indicators are considered key metrics to document the interruption of transmission of Onchocerca volvulus, the etiological agent of human onchocerciasis. Human landing collection is the standard employed for collection of the vectors for this parasite. Recent studies reported the development of traps that have the potential for replacing humans for surveillance of O. volvulus in the vector population. However, the key chemical components of human odor that are attractive to vector black flies have not been identified. Methodology/Principal Findings: Human sweat compounds were analyzed using GC-MS analysis and compounds common to three individuals identified. These common compounds, with others previously identified as attractive to other hematophagous arthropods were evaluated for their ability to stimulate and attract the major onchocerciasis vectors in Africa (Simulium damnosum sensu lato) and Latin America (Simulium ochraceum s. l.) using electroantennography and a Y tube binary choice assay. Medium chain length carboxylic acids and aldehydes were neurostimulatory for S. damnosum s.l. while S. ochraceum s.l. was stimulated by short chain aliphatic alcohols and aldehydes. Both species were attracted to ammonium bicarbonate and acetophenone. The compounds were shown to be attractive to the relevant vector species in field studies, when incorporated into a formulation that permitted a continuous release of the compound over time and used in concert with previously developed trap platforms. Conclusions/Significance: The identification of compounds attractive to the major vectors of O. volvulus will permit the development of optimized traps. Such traps may replace the use of human vector collectors for monitoring the effectiveness of onchocerciasis elimination programs and could find use as a contributing component in an integratedvector control/drug program aimed at eliminating river blindness in Africa

Stochastic linear programming for improved reservoir operations for multiple objectives in Burkina Faso, West Africa

A network of reservoirs and diversion structures in the Comoe River Basin in southwestern Burkina Faso, West Africa, provides municipal water supply and irrigation water for sugarcane agribusiness and a population of farmers. The region is characterized by severe intraseasonal and inter-annual variability with respect to precipitation and reservoir inflows. Reservoir operations are generally conservative, even during wet years. A stochastic linear programming model is introduced which translates seasonal streamflow and precipitation forecasts, in the form of a scenario tree, into optimal release schedules for reservoir operators to implement in real-time as forecasts and system conditions change. Goals include more efficient and equitable releases, and downstream flow maintenance. A VBA-based graphic user interface (GUI) is used to ensure implementation and ease of use by operators. © 2008 ASCE

Validation of a Remote Sensing Model to Identify <i>Simulium damnosum</i> s.l. Breeding Sites in Sub-Saharan Africa

<div><p>Background</p><p>Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict <i>S. damnosum</i> s.l. breeding sites.</p><p>Methodology/Principal Findings</p><p>Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of <i>S. damnosum</i> s.l. breeding habitat. All 30 sites with the spectral signature were found to contain <i>S. damnosum</i> larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained <i>S. damnosum</i> larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature.</p><p>Conclusions/Significance</p><p>This study suggests that a signature extracted from remote sensing images may be used to predict the location of <i>S. damnosum</i> s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement.</p></div

Spectrally decomposed signature of the <i>S. damnosum</i> s.l. larval riverine habitat pixel.

<p>The signature was extracted from 0.61 m² QuickBird satellite data, as described in the text. The figure depicts the wave band color reflectance ratio (i.e. pixel digital number) of the extracted spectral signature. Colors correspond to the bandwidths indicated in the figure.</p

<i>S. damnosum</i> s.l. aquatic habitat not predicted by the BRR model.

<p>The photo illustrates the hanging vegetation immersed in fast flowing water characteristic of the two breeding sites in the Achwa River not predicted by the BRR model.</p

Ground verification of predicted <i>S. damnosum</i> s.l. larval habitats.

<p>Panel A: Location of sites surveyed. Locations are presented as the Euclidian distance downstream from the start point of the survey (Lat 445861.2662, Lon 1224410.647). Red circles indicate locations predicted to be breeding sites by the model, while blue squares represent locations of other likely larval sites identified by the survey team as described in the text. Panel B: Larval counts from each survey point. Red bars represent larval counts from sites predicted by the model to represent larval habitats and blue bars (all zero) represent larval counts at the other sites surveyed.</p

Comparison of habitats predicted by the wet rock and dry rock/elevation change models.

<p>Potential <i>S. damnosum</i> s.l. breeding habitats were predicted from images collected from the Sarakawa river basin using the BRR model (small black dots) or using a the model based upon the signature for wet or dry Precambrian rock and a sufficient elevation change to support fast flowing water if present (large red dots).</p