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

Abstract

Inter-relationships among mosquito vectors, Plasmodium parasites, human ecology, and biotic and abiotic factors, drive malaria risk. Specifically, rural landscapes shaped by human activities have a great potential to increase the abundance of malaria vectors, putting many vulnerable people at risk. Understanding at which point the abundance of vectors increases in the landscape can help to design policies and interventions for effective and sustainable control. Using a dataset of adult female mosquitoes collected at 79 sites in malaria endemic areas in the Brazilian Amazon, this study aimed to (1) verify the association among forest cover percentage (PLAND), forest edge density (ED), and variation in mosquito diversity; and to (2) test the hypothesis of an association between landscape structure (i.e., PLAND and ED) and Nyssorhynchus darlingi (Root) dominance. Mosquito collections were performed employing human landing catch (HLC) (peridomestic habitat) and Shannon trap combined with HLC (forest fringe habitat). Nyssorhynchus darlingi abundance was used as the response variable in a generalized linear mixed model, and the Shannon diversity index (H') of the Culicidae community, PLAND, and the distance house-water drainage were used as predictors. Three ED categories were also used as random effects. A path analysis was used to understand comparative strengths of direct and indirect relationships among Amazon vegetation classes, Culicidae community, and Ny. darlingi abundance. Our results demonstrate that Ny. darlingi is negatively affected by H´ and PLAND of peridomestic habitat, and that increasing these variables (one-unit value at β0 = 768) leads to a decrease of 226 (P < 0.001) and 533 (P = 0.003) individuals, respectively. At the forest fringe, a similar result was found for H' (β1 = -218; P < 0.001) and PLAND (β1 = -337; P = 0.04). Anthropogenic changes in the Amazon vegetation classes decreased mosquito biodiversity, leading to increased Ny. darlingi abundance. Changes in landscape structure, specifically decreases in PLAND and increases in ED, led to Ny. darlingi becoming the dominant species, increasing malaria risk. Ecological mechanisms involving changes in landscape and mosquito species composition can help to understand changes in the epidemiology of malaria.

Fig 1. Map of Brazilian Amazonian biome (in red) in South America.

A: Köppen and Geiger Climate Classification; Af–Tropical Rainforest, Am–Tropical Monsoon, As–Tropical wet and dry, Aw–Savanna, Cfa–Humid subtropical, Cwa–Subtropical-dry winter. B: Brazilian Vegetation Class (IBGE, 2012); Anthropogenic–dominance of Poaceae, Verbanaceae, Lamiaceae, Solanaceae and Asteraceae botanical families; Tropical Moist Forest–dominance of Lecythidaceae and Vochysiaceae; Tropical Moist Forest Arecaceae–dominance of Lecythidaceae, Vochysiaceae and Arecaceae; Riverine and Marine Vegetation–Arecaceae, Solanaceae, Myrtaceae and Rhizophoraceae; Campinarama–Euphorbiaceae, Arecaceae, Humiriaceae and Fabaceae; Savana–Poaceae, Cyperaceae, Amarylidaceae and Xyridaceae; Seasonal Lowland Forest–Lauraceae, Lythraceae, Boraginaceae, Fabaceae and Myrtaceae. C: Amazonian ecoregions based on biogeography (https://ecoregions2017.appspot.com/) [100]. D: Quarterly Totals Precipitation (mm³) of June, July and August from 1977 to 2006 (http://cprm.gov.br). Reprinted from QGIS version 2.8 without any changes, under a CC BY license, with permission from PLOS ONE, original copyright 2020.

Fig 2. Study design scheme.

Large circle (red) represents the sampling unit, and smaller circles (blue) the collection points. A: peridomestic habitat (HLC), and B: forest fringe habitat (ST).

Fig 3. Culicidae species frequency displayed as a cloud for each of three ED categories (low, moderate and high) in forest fringe collections in rural areas of Amazonian Brazil.

Font size is proportional to the frequency of Culicidae species. Edge density categories: Low (0–1.5 m / ha x 100); moderate (1.5–2.0 m / ha x 100); high (2.0–3.5 m / ha x 100).

Fig 4

Correlation matrix among Ny. darlingi abundance, PLAND, ED, richness, DW, diversity indices (richness, Shannon, Simpson and Berger-Parker), Amazonian vegetation classes (Atp: Anthropogenic; OTMFA: Open Tropical Moist Forest with Arecaceae dominance; TMF: Tropical Moist Forest; Cpn: Campinarana), and landscape structures (A: PLAND ≤ 50% and ED < 0.015 m/ha; B: PLAND ≤ 50% and ED ≥ 0.015 m/ha; C: PLAND > 50% and ED ≥ 0.015 m/ha). PLAND: percentage of forest cover; ED: edge density; DW: distance of household from water drainage network.

Fig 5

Structural equation model diagram to describes the relationships between changes in Ny. darlingi abundance with each independent variable: Shannon-index, PLAND, ED, landscape structure categories (A: PLAND ≤ 50% and ED < 0.015 m/ha; B: PLAND ≤ 50% and ED ≥ 0.015 m/ha; C: PLAND > 50% and ED ≥ 0.015 m/ha; D: PLAND > 50% and ED < 0.015 m/ha), Amazonian vegetation class (Atp: Anthropogenic; OTMF: Open Tropical Moist Forest; OTMFA: Open Tropical Moist Forest with Arecaceae dominance; TMF: Tropical Moist Forest; Cpn: Campinarana) and DW. Dashed lines represent a reciprocal path, and solid line one direction. Red arrows (positive coefficient) and blue arrows (negative coefficient) represent the significant path coefficients (P < 0.05).

Fig 6. Canonical correspondence analysis of mosquito assemblages and landscape structure classifications at each sampling unit.

Open landscape (A) is represented by black circles, fragmented open land (B) is represented by red, fragmented forest (C) is represented by green, and forested (D) is represented by blue circles. The length of the arrow representing the strength of the relationship. The yellow triangle represents Ny. darlingi. A: PLAND ≤ 50% and ED < 0.015 m/ha; B: PLAND ≤ 50% and ED ≥ 0.015 m/ha; C: PLAND > 50% and ED ≥ 0.015 m/ha; D: PLAND > 50% and ED < 0.015 m/ha.