Physico-chemical and biological characterization of anopheline mosquito larval habitats (Diptera: Culicidae): implications for malaria control

Particle and Fibre Toxicology

Peter LM Goethals⁶  Luc De Meester¹  Worku Legesse⁴  Sophie O Vanwambeke⁵  Niko Speybroeck⁷  Luc Duchateau³  Abdulhakim Ahmed⁸  Pieter Boets⁶  Delenasaw Yewhalaw²  Seid Tiku Mereta⁶ 

[1] Laboratory of Aquatic Ecology, Evolution and Conservation, University of Leuven, Ch. Deberiotstraat 32, B-3000 Leuven, Belgium;Department of Biology, Jimma University, Jimma, Ethiopia;Department of Comparative Physiology and Biometrics, Ghent University, Ghent, Belgium;Department of Environmental Engineering, University of Connecticut, Storrs - Mansfield, USA;Georges Lemaître Centre for Earth and Climate Research, Earth & Life Institute, Université Catholique de Louvain, Place Pasteur, 3, 1348 Louvain-la-Neuve, Belgium;Laboratory of Environmental Toxicology and Aquatic Ecology, Ghent University, J. Plateaustraat 22, B-9000 Ghent, Belgium;Institute for Health and Society (IRSS), Université Catholique de Louvain, Brussels, Belgium;Department of Geography, Jimma University, Jimma, Ethiopia

关键词: Mosquito larvae;    Mosquito control;    Macroinvertebrate predators;    Generalized linear model;    Decision trees;   

Others  :  823946
DOI  :  10.1186/1756-3305-6-320

 received in 2013-04-17, accepted in 2013-10-25,  发布年份 2013

【 摘 要 】

Background

A fundamental understanding of the spatial distribution and ecology of mosquito larvae is essential for effective vector control intervention strategies. In this study, data-driven decision tree models, generalized linear models and ordination analysis were used to identify the most important biotic and abiotic factors that affect the occurrence and abundance of mosquito larvae in Southwest Ethiopia.

Methods

In total, 220 samples were taken at 180 sampling locations during the years 2010 and 2012. Sampling sites were characterized based on physical, chemical and biological attributes. The predictive performance of decision tree models was evaluated based on correctly classified instances (CCI), Cohen’s kappa statistic (κ) and the determination coefficient (R²). A conditional analysis was performed on the regression tree models to test the relation between key environmental and biological parameters and the abundance of mosquito larvae.

Results

The decision tree model developed for anopheline larvae showed a good model performance (CCI = 84 ± 2%, and κ = 0.66 ± 0.04), indicating that the genus has clear habitat requirements. Anopheline mosquito larvae showed a widespread distribution and especially occurred in small human-made aquatic habitats. Water temperature, canopy cover, emergent vegetation cover, and presence of predators and competitors were found to be the main variables determining the abundance and distribution of anopheline larvae. In contrast, anopheline mosquito larvae were found to be less prominently present in permanent larval habitats. This could be attributed to the high abundance and diversity of natural predators and competitors suppressing the mosquito population densities.

Conclusions

The findings of this study suggest that targeting smaller human-made aquatic habitats could result in effective larval control of anopheline mosquitoes in the study area. Controlling the occurrence of mosquito larvae via drainage of permanent wetlands may not be a good management strategy as it negatively affects the occurrence and abundance of mosquito predators and competitors and promotes an increase in anopheline population densities.

【 授权许可】

   
2013 Mereta et al.; licensee BioMed Central Ltd.

【 图 表 】

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