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1 July 2008 A Web-based Relational Database for Monitoring and Analyzing Mosquito Population Dynamics
Yves Sucaet, John Van Hemert, Brad Tucker, Lyric Bartholomay
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Abstract

Mosquito population dynamics have been monitored on an annual basis in the state of Iowa since 1969. The primary goal of this project was to integrate light trap data from these efforts into a centralized back-end database and interactive website that is available through the internet at http://iowa-mosquito.ent.iastate.edu. For comparative purposes, all data were categorized according to the week of the year and normalized according to the number of traps running. Users can readily view current, weekly mosquito abundance compared with data from previous years. Additional interactive capabilities facilitate analyses of the data based on mosquito species, distribution, or a time frame of interest. All data can be viewed in graphical and tabular format and can be downloaded to a comma separated value (CSV) file for import into a spreadsheet or more specialized statistical software package. Having this long-term dataset in a centralized database/website is useful for informing mosquito and mosquito-borne disease control and for exploring the ecology of the species represented therein. In addition to mosquito population dynamics, this database is available as a standardized platform that could be modified and applied to a multitude of projects that involve repeated collection of observational data. The development and implementation of this tool provides capacity for the user to mine data from standard spreadsheets into a relational database and then view and query the data in an interactive website.

Yves Sucaet, John Van Hemert, Brad Tucker, and Lyric Bartholomay "A Web-based Relational Database for Monitoring and Analyzing Mosquito Population Dynamics," Journal of Medical Entomology 45(4), 775-784, (1 July 2008). https://doi.org/10.1603/0022-2585(2008)45[775:AWRDFM]2.0.CO;2
Received: 20 December 2007; Accepted: 28 March 2008; Published: 1 July 2008
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KEYWORDS
cyberinfrastructure
ecoinformatics
ecology
mosquito
population dynamics
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