DOI: 10.6084/m9.figshare.3980400
title: An. darlingi modeling dataset

description: <b>Entomological data and Trap Position</b>: Mosquitoes were collected during the dry seasons in 2012 (September 3–November 25; 12 weeks), 2013 (September 2–November 24; 12 weeks), and 2014 (September 1–October 26; 8 weeks) from eight different sites that varied by year. Sites were selected from field expertise and followed a longitudinal transect that maximized heterogeneity of the landscape and lifestyle characteristics of the population. Trapping sessions were conducted on two non-consecutive nights per week, between 6:00 pm and 8:00 am, by using Mosquito Magnet® traps (Woodstream Corporation, Lititz, PA) baited with octenol (MMoct). Such traps have previously been proven useful to monitor the spatial and temporal abundance of malaria vectors in French Guiana. Mosquitoes were stored at -20 °C until counting and morphological identification. To achieve a weekly cartographic output and to smooth variation between collection nights, the two bi-weekly observations were averaged to approximate a daily number of specimens and then multiplied by seven to approximate a weekly number of specimens. In all, 165 weekly approximated <i>An. darlingi </i>density records across the eight study sites was finally available for analyses, which was slightly less than our expected maximum of 184, owing to the mechanical failure of traps. Weekly <i>An. darlingi</i> densities were allocated to three classes following the tercile method: “1" "Low densities” (first tercile), "2" “Medium densities” (second tercile), and "3" “High densities” (third tercile). Since our activities were not conducted in a protected area (not a national park or a regional nature reserve), no specific permission was required, and field studies did not involve endangered or protected species.<br><b>Land Cover Map: </b>A SPOT-5 image acquired on October 14, 2012, with four color channels (red, green, near-infra-red, and middle infrared) was selected to characterize the landscape of the study area. One image was sufficient to cover the eight trapping sites. However, the presence of clouds required the posterior use of a second SPOT-5 image (July 22, 2013) in order to fill the missing data (5% of the total study area) and obtain a spatially complete product. A land cover map of the study area was produced based on field observations and a supervised training approach with maximum likelihood classification. The classification included five land cover types identified as “built, roads, and bare soils”; “low vegetation”; “forest”; “very dense forest”; and “water.” A 7 × 7 pixel mode filter (i.e., each pixel value being replaced by its most common neighbor in a 7 × 7 cell moving window) was applied to the classification to reduce noise. BD-Topo® 2012 (IGN, the French National Institute of Geographic and Forest Information) was used to separate the “built” surfaces and “roads and bare soil” surfaces, resulting in a six-class land cover map.<br><b>Meteorological Data: </b>Daily meteorological records were obtained from the Meteo-France weather station located in the city center of Saint-Georges de l’Oyapock.<br> <br>