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Open Access Research article

Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region

Emmanuel Roux1*, Pascal Gaborit2, Christine A Romaña3, Romain Girod2, Nadine Dessay1 and Isabelle Dusfour2

Author Affiliations

1 ESPACE-DEV, UMR228 IRD/UM2/UR/UAG, Institut de Recherche pour le Développement, Maison de la Télédétection, 500 rue Jean-François Breton, 34093 Montpellier Cedex 5, France

2 Institut Pasteur de la Guyane, Unité d’Entomologie Médicale, 23 Avenue Pasteur, B.P. 6010, 97306 Cayenne Cedex, French Guiana

3 Université Paris Descartes/PRES Sorbonne Paris-Cité, 19 rue de Dantzig, 75015 Paris, France

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BMC Ecology 2013, 13:45  doi:10.1186/1472-6785-13-45

Published: 1 December 2013

Abstract

Background

Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum.

Results

We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value << 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001).

Conclusions

The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.