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Spatial clustering and associations of two savannah tsetse species, Glossina morsitans submorsitans and Glossina pallidipes (Diptera: Glossinidae), for guiding interventions in an adaptive cattle health management framework

Published online by Cambridge University Press:  27 May 2010

A. Sciarretta*
Affiliation:
Department of Animal, Plant and Environmental Science, University of Molise, Via De Sanctis, I-86100Campobasso, Italy
Getachew Tikubet
Affiliation:
Yeha Natural Resource Management Institute for Eastern Africa (YNRMI-EA), Addis Ababa, Ethiopia
J. Baumgärtner
Affiliation:
DiPSA, University of Milano, Via Celoria 2, I-20133Milano, Italy
Melaku Girma
Affiliation:
Yeha Natural Resource Management Institute for Eastern Africa (YNRMI-EA), Addis Ababa, Ethiopia
P. Trematerra
Affiliation:
Department of Animal, Plant and Environmental Science, University of Molise, Via De Sanctis, I-86100Campobasso, Italy
*
*Author for correspondence Fax: 0039 0874 404855 E-mail: sciarretta@unimol.it

Abstract

The paper deals with tsetse (family Glossinidae) control and aims at improving the methodology for precision targeting interventions in an adaptive pest management system. The spatio-temporal distribution of Glossina morsitans submorsitans Newstead, and Glossina pallidipes Austen, at Ethiopia's Keto pilot site, is analyzed with the spatial analysis by distance indices (SADIE) methodology that focus on clustering and spatial associations between species and between sexes. Both species displayed an aggregated distribution characterised by two main patches in the south and an extended gap in the north. Spatial patterns were positively correlated and stable in most cases, with the exception of the early dry season and the short rainy season when there were differences between the species and sexes. For precision targeting interventions, the presented methods here are more effective than the previously used geostatistical analyses for identifying and delimiting hot spots on maps, measuring shapes and sizes of patches, and discarding areas with low tsetse density. Because of the improved knowledge on hot spot occurrences, the methods allow a better delimitation of the territory for control operations and a more precise computation of the number of the relatively expensive traps used for monitoring and control purposes.

Type
Research Paper
Copyright
Copyright © Cambridge University Press 2010

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