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<datestamp>2014-12-09</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.</title>
<creator>Roux, Emmanuel</creator>
<creator>Gaborit, Pascal</creator>
<creator>Romaña, Christine A</creator>
<creator>Girod, Romain</creator>
<creator>Dessay, Nadine</creator>
<creator>Dusfour, Isabelle</creator>
<contributor>Espace pour le Développement (ESPACE-DEV) ; Université Montpellier 2 - Sciences et Techniques (UM2) - Université des Antilles et de la Guyane (UAG) - Institut de recherche pour le développement [IRD] - Université de la Réunion</contributor>
<contributor>Institut Pasteur de la Guyane Française ; Institut Pasteur de la Guyane - Réseau International des Instituts Pasteur</contributor>
<contributor>Université Paris Descartes/PRES Sorbonne Paris-Cité ; Université Paris Descartes - Paris 5 (UPD5) - PRES Sorbonne Paris Cité</contributor>
<contributor>Unité d'Entomologie Médicale ; Institut Pasteur de la Guyane</contributor>
<contributor>This study was sponsored by the General Delegation of French Overseas Regions (Délégation Générale à l'Outre-Mer) within the framework of the project "Bioecology of the vectors of malaria in Cacao, French Guiana: towards assessing the exposure risk and improving the vector control". The study was also supported by OSE-Guyamapá, a cross-border cooperation project funded by the operational Program "PO-Amazonie" of the European Regional Development Fund in French Guiana.</contributor>
<description>International audience</description>
<source>BMC Ecology</source>
<publisher>BioMed Central</publisher>
<identifier>pasteur-00914104</identifier>
<identifier>https://hal-riip.archives-ouvertes.fr/pasteur-00914104</identifier>
<identifier>https://hal-riip.archives-ouvertes.fr/pasteur-00914104/document</identifier>
<source>https://hal-riip.archives-ouvertes.fr/pasteur-00914104</source>
<source>BMC Ecology, BioMed Central, 2013, 13 (1), pp.45. <10.1186/1472-6785-13-45></source>
<identifier>DOI : 10.1186/1472-6785-13-45</identifier>
<identifier>PUBMED : 24289184</identifier>
<language>en</language>
<subject>[SDE.BE] Environmental Sciences/Biodiversity and Ecology</subject>
<subject>[SDV.BA.ZI] Life Sciences/Animal biology/Invertebrate Zoology</subject>
<subject>[INFO.INFO-TI] Computer Science/Image Processing</subject>
<subject>[STAT.AP] Statistics/Applications</subject>
<type>Journal articles</type>
<description lang=en>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.</description>
<date>2013-12-01</date>
</dc>
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