Anthropogenic landscape decreases mosquito biodiversity and drives malaria vector proliferation in the Amazon rainforest

Mosquito collection Collections were conducted outdoors in the peridomestic habitat (approximately five meters from the household entrance) using human landing catch (HLC) and in the forest fringe habi- tat (approximately 10 meters into the forest interface with open areas) with Shannon trap using light and human attraction (ST) [57]. There were two collection points for each sampling unit and HLC and ST collections were conducted simultaneously. Mosquito data from HLC and ST were summed and employed as the field data representative for each sampling unit. Therefore, the total of mosquitoes collected on HLC and ST were evaluated together and used as fixed variable in the models at 1 km radius for each sampling unit. Sampling was performed once between 18:00 and 0:00h, from April to November 2016–17, during the wet-dry transition, dry season, and dry-wet season (S1 Table in S1 File). The only exception to the simultaneous collections was during heavy rain and /or strong wind. Mosqui- toes were collected with a manual vacuum aspirator. Two collectors worked each night inn each habitat, using HLC in the peridomestic area and ST in the forest fringe; each unit was sampled once. Variation in the number of collectors was due to their availability during field trips. Every hour, mosquitoes were euthanized with ethyl acetate (C4H8O2) vapors in the field and stored in silica gel identified by sampling unit number, habitat, date, and hour for subse- quent species identification using the morphological identification key of Forattini [58]. The

latitude and longitude of each collection point was recorded in the field with a GPS unit, using geodetic, global geographic coordinate WGS84. The decision for collecting mosquitoes with ST at the forest fringe habitat considered the effectiveness of the trap for sampling Culicidae diversity [59]. These two collection methods have been compared previously in the Amazonian forest, and abundance and presence of Ny. darlingi were similar [60]. The sampling effort for each collection method and habitat was the same. Landscape metrics Landscape metrics were generated from a Sentinel 2A satellite imagery (European Space Agency (ESA)) from the day nearest to the date of collection. with a spatial resolution of 10 m. Selection of the images included 1) the lowest percentage of clouds, and 2) as near as possible to the field collection date. The images were downloaded from the ESA (https://www.esa.int/ ESA) in raster format and graded, with radiometric and atmospheric corrections, by means of an algorithm developed by ESA and implemented in Sen2Cor software [61]. The satellite images were classified in two land-use classes (forest and non-forest) through a supervised classification, using the maximum likelihood method. All analyzes were performed in QGIS, version 2.8 without any changes (QGIS is licensed under Creative Commons Attribution- ShareAlike 3.0 license (CC BY-SA) (https://creativecommons.org/licenses/by-sa/3.0/)). Percentage of forest cover (PLAND) and forest edge density (ED) were calculated for all 79

sampling units (1 km radius). Details on how to calculate these metrics can be found in the S1 File [62]. PLAND and ED were also measured on a subtended circle of 0.5 km radius (0.8 km2), measured around each collection point (HLC/ST). These radii were chosen because in a study performed in Malaysian Borneo, Brock and collaborators [63] demonstrated that the optimal radius for addressing the edge effects on P. knowlesi malaria occurrence was 0.5 km, but the proportion of cleared land within 1 km was low. PLAND and ED were chosen because of the ecological characteristics of Ny. darlingi, which have an affinity for partly shaded habitats for oviposition and development of immature stages in ground pools and slow-moving streams at forest edges, as reviewed by Hiwat and Bretas [34]. These metrics were used to assess the effects of landscape elements on mosquito PLOS ONE Anthropogenic landscape and mosquito biodiversity drives malaria vector proliferation PLOS ONE | https://doi.org/10.1371/journal.pone.0245087 January 14, 2021 5 / 25