Modeling Habitat and Environmental Factors Affecting Mosquito Abundance in Chesapeake, Virginia
type: CreativeWork
description: The models I present in this dissertation were designed to enable mosquito control agencies in the mid-Atlantic region that oversee large jurisdictions to rapidly track the spatial and temporal distributions of mosquito species, especially those species known to be vectors of eastern equine encephalitis and West Nile virus. I was able to keep these models streamlined, user-friendly, and not cost-prohibitive using empirically based digital data to analyze mosquito-abundance patterns in real landscapes. This research is presented in three major chapters: (II) a series of semi-static habitat suitability indices (HSI) grounded on well-documented associations between mosquito abundance and environmental variables, (III) a dynamic model for predicting both spatial and temporal mosquito abundance based on a topographic soil moisture index and recent weather patterns, and (IV) a set of protocols laid out to aid mosquito control agencies for the use of these models. The HSIs (Chapter II) were based on relationships of mosquitoes to digital surrogates of soil moisture and vegetation characteristics. These models grouped mosquitoes species derived from similarities in habitat requirements, life-cycle type, and vector competence. Quantification of relationships was determined using multiple linear regression models. As in Chapter II, relationships between mosquito abundance and environmental factors in Chapter III were quantified using regression models. However, because this model was, in part, a function of changes in weather patterns, it enables the prediction of both 'where' and 'when' mosquito outbreaks are likely to occur. This model is distinctive among similar studies in the literature because of my use of NOAA's NEXRAD Doppler radar (3-hr precipitation accumulation data) to quantify the spatial and temporal distributions in precipitation accumulation. \ Chapter IV is unique among the chapters in this dissertation because in lieu of presenting new research, it summarize…
abstract: The models I present in this dissertation were designed to enable mosquito control agencies in the mid-Atlantic region that oversee large jurisdictions to rapidly track the spatial and temporal distributions of mosquito species, especially those species known to be vectors of eastern equine encephalitis and West Nile virus. I was able to keep these models streamlined, user-friendly, and not cost-prohibitive using empirically based digital data to analyze mosquito-abundance patterns in real landscapes. This research is presented in three major chapters: (II) a series of semi-static habitat suitability indices (HSI) grounded on well-documented associations between mosquito abundance and environmental variables, (III) a dynamic model for predicting both spatial and temporal mosquito abundance based on a topographic soil moisture index and recent weather patterns, and (IV) a set of protocols laid out to aid mosquito control agencies for the use of these models. The HSIs (Chapter II) were based on relationships of mosquitoes to digital surrogates of soil moisture and vegetation characteristics. These models grouped mosquitoes species derived from similarities in habitat requirements, life-cycle type, and vector competence. Quantification of relationships was determined using multiple linear regression models. As in Chapter II, relationships between mosquito abundance and environmental factors in Chapter III were quantified using regression models. However, because this model was, in part, a function of changes in weather patterns, it enables the prediction of both 'where' and 'when' mosquito outbreaks are likely to occur. This model is distinctive among similar studies in the literature because of my use of NOAA's NEXRAD Doppler radar (3-hr precipitation accumulation data) to quantify the spatial and temporal distributions in precipitation accumulation. \ Chapter IV is unique among the chapters in this dissertation because in lieu of presenting new research, it summarize…
author: Bellows, Alan Scott
keywords: Culiseta melanura, Mosquitoes, Virginia, West Nile virus, Ecology and Evolutionary Biology, Remote Sensing
date published: 2007-07-01T07:00:00Z
date modified: 2026-07-24T03:34:53Z
provider: Old Dominion University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Old Dominion University