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PATTERNS OF ABUNDANCE ACROSS AN URBAN-RURAL GRADIENT FOR COMMONLY FOUND INDIGENOUS ARTHROPODS

Abstract Proof of concept for a continuous environmental sampling methodology that employs common terrestrial arthropods as environmental samplers was tested by analyzing pitfall, malaise and black light captures over a six month period over a replicated urban-suburban-rural gradient in Central Virginia. All arthropods captured at the nine sites were identified and assigned to aquatic, vegetation, or soil groups based on their association with these microhabitats. To offset variability in arthropod life history patterns and species abundance within habitat types, arthropod categories based on presence/absence data over the six month period were constructed to provide for sampling reliability within each microhabitat type. Arthropod categories ranged from single abundant species and families to synthetic groupings based on microhabitat associations (e.g., “soil beetles”), all of which could be easily identified. Mean weekly captures of individuals in each resulting category were compared within and among the nine sites using GLM or ranks analyses. Overall and weekly mean capture rates in the aquatic (two categories), soil (seven categories) and vegetation (11 categories) microhabitats were similar within each habitat type. With the exception of the two aquatic category members (midges and caddisflies), overall, monthly and weekly mean capture rates of all arthropod categories were highest in suburban and lowest in urban habitats. Results demonstrate reliability of the arthropod categories constructed and provide ground truthing for a continuously deployable and user-friendly arthropod-based system for monitoring environmental agents.

Identiferoai:union.ndltd.org:vcu.edu/oai:scholarscompass.vcu.edu:etd-2813
Date17 April 2009
CreatorsJones, David
PublisherVCU Scholars Compass
Source SetsVirginia Commonwealth University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations
Rights© The Author

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