Forests as Natural Barrier or Facilitators? The Role of Vegetation Structure in Mosquito Dispersal Patterns
DOI:
https://doi.org/10.70882/josrar.2026.v3i1.155Keywords:
Forest fragmentation, Vegetation structure, Mosquito dispersal, Malaria, Dengue, Landscape ecology, Microclimate, Remote sensingAbstract
Mosquito-borne diseases such as malaria, dengue, Zika, and chikungunya continue to pose major global health challenges, particularly across tropical and subtropical regions. While the role of climate, human mobility, and land use change in shaping disease transmission has been widely studied, the influence of forest vegetation structure on mosquito dispersal remains underexplored. Forests can simultaneously act as natural barriers, through dense canopy cover, lower temperatures, and reduced light, and as facilitators when fragmented or disturbed, creating transitional ecotones conducive to vector survival and flight. Recent research integrating landscape ecology, entomology, and remote sensing has revealed that vegetation heterogeneity, canopy height, and microclimate gradients directly mediate mosquito flight range, host-seeking behavior, and pathogen transmission potential. For example, Anopheles species often exploit partially cleared forest edges, while Aedes mosquitoes thrive in peri-urban forest mosaics that combine vegetation cover with artificial breeding habitats. Using Light Detection and Ranging (LiDAR)-based canopy measurements, Normalized Difference Vegetation Index (NDVI) modeling, and mark–release–recapture experiments, scientists are quantifying how vegetation structure predicts vector mobility across landscapes. This review synthesizes current knowledge (2021–2025) on how forest attributes modulate mosquito dispersal and vector-borne disease risks, emphasizing tropical ecosystems in Africa, South America, and Southeast Asia. We discuss mechanistic pathways linking vegetation and vector ecology, evaluate forest management implications for disease prevention, and identify future research priorities integrating remote sensing and ecological modeling.
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