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Seasonal changes in a cactus-hoverfly (Diptera: Syrphidae) network

Authors

  • ANA P. MARTÍNEZ-FALCÓN,

    1. Instituto de Biodiversidad CIBIO, Universidad de Alicante, Campus Universitario San Vicente del Raspeig, Alicante, España
    2. Centro de Investigaciones Biológicas, Universidad Autónoma del Estado de Hidalgo, Pachuca, México
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  • M. ÁNGELES MARCOS-GARCÍA,

    1. Instituto de Biodiversidad CIBIO, Universidad de Alicante, Campus Universitario San Vicente del Raspeig, Alicante, España
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  • CECILIA DÍAZ-CASTELAZO,

    1. Interacciones Multitróficas, Instituto de Ecología, A.C. Xalapa, México
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  • VICTOR RICO-GRAY

    Corresponding author
    1. Interacciones Multitróficas, Instituto de Ecología, A.C. Xalapa, México
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Victor Rico-Gray, Interacciones Multitróficas, Instituto de Ecología, A.C. Xalapa, Veracruz 91070, México. E-mail: victor.rico@inecol.edu.mx, vricogray@yahoo.com

Abstract

1. We analysed a cacti-syrphid community focusing on the exploitation of decaying cacti resources by the flies, i.e. if exploitation exhibited a nested topology as a structural pattern, or whether it was temporally random. If availability of cactus resources was predictable during the rainy season, it would then be exploited by a more structured community, or as resource availability would be unpredictable during the dry season, we should expect it to be exploited by a random community.

2. We registered 12 Copestylum species (9 in dry and 11 in rainy season). Four cactus species were recorded per season, three were shared between seasons.

3. The community of Copestylum larvae in the rainy season was not randomly assembled but highly nested, revealing a highly structured pattern of resource use. It exhibited a random organization for the dry season. The high nestedness value obtained for the rainy season suggests that factors along with competition must play a major role in determining community structure.

4. Succession in the cacti-syrphid community mediated by microorganisms involved in necrosis is an important factor structuring nested subsets. The studied networks were small, which may limit the power of the analysis, and strong conclusions could also be limited.

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