SimPhy: a simulation game to lessen the impact of phytosanitaries on health and the environment--the case of Merja Zerga in Morocco.

Diffuse phytosanitary pollution is a complex phenomenon to manage. Reducing this type of pollution is one of today's key socio-economic and environmental challenges. At the regional level, few approaches enable the actors concerned to implement agricultural management strategies to reduce the use and impact of phytosanitary products. Our research problem focused on the consequences of intensive agriculture and, in particular, how to evaluate the impact of phytosanitary products on human health and the environment. In this article, we present the SimPhy simulation game which places the actors from a given region directly into a situation in which they manage farms whilst under pressure to reduce phytosanitaries (quantity and toxicity). The application focused on the Merja Zerga catchment area in Morocco. The region is dominated by intensive agriculture which is located upstream from a Ramsar-classified wetland area. The SimPhy simulation game is based on a decision support system-type tool. It allows us to anticipate the impact of regulations on farming systems. It also enables us to analyse the consequences of the actors' strategies on farm economies, human health and the quality of ecosystems. Initial results from the SimPhy simulation game enabled the technicians from Agricultural Development Center (CDA) themselves to learn about managing agricultural production systems in a dynamic and interactive fashion. With the simulation game, it was possible to learn about the farmer's ability to adapt to new regulatory constraints, and the involved consequences for toxicity risks for human health and the environment.

Fragmentation analysis for prediction of suitable habitat for vectors: example of riverine tsetse flies in Burkina Faso.

Tsetse flies are the cyclic vectors of sleeping sickness and African animal trypanosomosis. The possibility to classify the natural habitat of riverine tsetse species is explored in the Mouhoun River basin, Burkina Faso: the objectives were to discriminate the riverine forests community types and their fragmentation levels by using Landsat 7 enhanced thematic mapper images, to map tsetse densities. Glossina palpalis gambiensis Vanderplank 1949 (Diptera: Glossinidae) and G. tachinoides Westwood, 1850 are the vectors of trypanosomoses in this area. After a supervised classification, the community types were discriminated using the water area in 400-m-wide polygons around the river. A fragmentation analysis of the swamp forest unit, cross-tabulated with the community types, lead to identification of the final landscapes where tsetse apparent densities (ADT) were implemented using a training data set of 608 trap locations. The predicted ADT were then compared with an independent validation data set of 78 trap locations. The correlation between the model predictions and the validation data set was high, validating this approach (P < 0.001). The riverine forest community type and fragmentation level are critical factors for riverine tsetse species, which should be taken into consideration to map their suitable habitat.