The W-Arly-Pendjary (WAP) parks, a complex of three protected areas that covers three different countries in West-Africa: Benin, Burkina-Faso and Niger.
The WAP complex counts nineteen ecological sites distributed in three protected areas. It represents 25% of the sub-regions savannah habitats, constitutes the most important remaining area for elephant conservation in Africa and protects more than 370 bird species, 94 insect species, 80 fish species and other various species of reptiles and amphibians (UNDP, 2004). But many of these species are threatened due to the unsustainable practices in the region. The unsustainable practices are poaching, uncontrolled bushfires, agricultural encroachments, unsustainable harvesting of Non Timber Forest Products (NTFPs), timber and fish overexploitation, etc. Using unmanned aerial vehicles, drones, the present project tackles this issue in an innovative way. It will contribute to the sustainable management of this protected area by providing scientific evidences that will support different sustainable options.
The first research project titled “Coevolution options for the sustainability of the WAP” analyze different socioeconomic activities that could co-evolve sustainably with the natural environmental. This research project will answer to a crucial question: How does the scale of the various economic activities around the parks affect the base of natural resources? It will provide the trade-offs between the net economic value of the activities and the resources loss and propose different sustainable paths for the exploitation of these resources.
The other researches for this project analyze the use of drones for agriculture. Agricultural encroachment affects the biodiversity in protected areas. Agricultural production in the riparian villages, as well as in many African countries, is critical to both food security and economic development especially in the context of climate change. According to Wegner and Zwart (2011) and McKenzie and Williams (2015), by 2050, farmers in this part of the world would need to double their agricultural production in order to meet the increasing food needs of their growing population in a context where their technology is still rudimentary and their farming system is stressed by climate change conditions. The solutions needed include low-input and high-efficiency technologies that can manage and distribute the limited resources available optimally in other words precision agriculture technologies. These technologies also need to have a reduced negative impact on the environment and on farmers’ health. We think drones can be used to help farmers in developing countries experience the benefits of precision agriculture.
The research project “Drones for precision agriculture in developing countries: comparative evaluation of pesticide spraying drones and manual spraying systems” use a field experiment to test how drones can be adapted to farmers in developing countries and developed countries needs for pesticide spraying. The field experiment consists on comparing a pesticide spraying drone performance with the performance of an operator who uses a manual pesticide sprayer as used by farmers in developing countries. We use fluorescent tracer technique to evaluate/compare the two methods of pesticides sprays. Fluorescent tracer is a non-toxic chemical used to mimic pesticide contamination on skin, clothing, and surfaces.
Under normal lighting, when mixed, diluted and applied (like pesticides) it cannot be seen. Under a blacklight tracer, it is visible and can reveal areas of potential exposure. The two sprayers to be compared are filled with water and fluorescent tracers. The time needed to spray different experimental areas is compared for both of them. Dermal exposure will is evaluated. Soils deposits from the fluorescent tracer (replacing the pesticides applications) are also compared. The other costs associated with each of the spraying modes in developing countries (equipment rental, custom application, hourly employee wages, etc.) are also considered in the various comparison analyses conducted.
Recent advancements in Global Positioning Systems (GPS), geographic information systems (GIS), remote sensing, telecommunications, miniaturization of computer components, and automation have made possible the development of low-cost drones. In agriculture, drones offer new possibilities for the adaptation of precision to small-scale farmer’s needs. The services provided to farmers by precision farming systems can be replicated with drones if the necessaries technologies are integrated into the drones. Recent developments of the drone technology show that this is feasible. The imaging system, for example, can allow farmers to monitor their crop health (density, height, nutrient or water stress), estimate crop yield, sense soil characteristics (N, P, K, etc.) and identify and react quicker to threats (weeds, pests, fungi). With the smart crop-spraying agricultural drones farmers can accurately apply fertilizer, liquid pesticides and herbicides only where it is needed.
Drones might be able to do it faster than manual spraying operations and more accurately since the drones can automatically keep a record of its past coordinates and eliminate overlay application. Are farmers willing to pay for the drone services and how much? What is the impact of these services on farmers’ livelihood? First, we will conduct experiments with households living in and around the WAP to learn about their willingness to pay for the drone services and how this varies across households. Second we will use a cluster-randomized controlled trial (c-RCT) to evaluate the effectiveness of the drone services on their livelihood. Four groups will benefit from different levels of drone services and will be compared to a control group which will receive no intervention. The villages will be randomly selected and the interventions will be randomly assigned. Agricultural activity performances, time allocation and expenses on foods, health, and education will be assessed by questionnaire administration.