Diving behavior in Anopheles gambiae (Diptera: Culicidae): avoidance of a predacious wolf spider (Araneae: Lycosidae) in relation to life stage and water depth.

It has been suggested that mosquito larvae and pupae dive to avoid predators. We tested this predator-avoidance hypothesis by using immature Anopheles gambiae Giles (Diptera: Culicidae) and the wolf spider Pardosa messingerae (Stand) (Araneae: Lycosidae). Because previous studies have suggested that wolf spiders are poor predators of immature mosquitoes, we first examined the predatory ability of the wolf spider and found that the spider was effective at capturing all stages of larvae and pupae. The mortality from experimental cups containing deep water increased with the age of mosquitoes, with the exception of pupae. In contrast, this trend was not observed in shallow water. In particular, mortality was significantly lower in deep water during the second instar. During the third instar, the opposite trend was observed. When the effect of cannibalism was excluded by subtracting the number of missing mosquitoes for the treatment without spiders from those with spiders, the cannibalism corrected mortality was significantly lower in deep water during the second instar. The duration of diving by larvae and pupae decreased with age. With the exception of first instar, diving frequency also decreased with age. We postulate that this diving behavior allows An. gambiae to escape predation by wolf spiders, which supports the predator-avoidance hypothesis. This study indicates some important implications for vector control

Predatory capacity of a shorefly, Ochthera chalybescens, on malaria vectors

<p>Abstract</p> <p>Background</p> <p>Since <it>Ochthera chalybescens </it>had been reported to prey on African malaria vectors, the predatory capacity of adults of this species on <it>Anopheles gambiae </it>sensu stricto was explored.</p> <p>Method</p> <p>Predatory capacity of this fly on <it>A. gambiae </it>s.s. was tested at all developmental stages, including the adult stage in the laboratory setting. Effects of water depth on its predatory capacity were also examined.</p> <p>Results</p> <p>This study revealed that <it>O. chalybescens </it>preyed on mosquitoes at all life stages except eggs. It was able to prey on an average of 9.8 to 18.8 mosquito larvae in 24 hrs. Mosquito larva size and water depth did not affect predatory capacity. However, the predacious fly preyed on significantly more 2^nd-instar larvae than on pupae when larvae and pupae were both available.</p> <p>Conclusion</p> <p><it>Ochthera chalybescens </it>is, by all indications, an important predator of African malaria vectors.</p

Topographic models for predicting malaria vector breeding habitats: potential tools for vector control managers

BackgroundIdentification of malaria vector breeding sites can enhance control activities. Although associations between malaria vector breeding sites and topography are well recognized, practical models that predict breeding sites from topographic information are lacking. We used topographic variables derived from remotely sensed Digital Elevation Models (DEMs) to model the breeding sites of malaria vectors. We further compared the predictive strength of two different DEMs and evaluated the predictability of various habitat types inhabited by Anopheles larvae.MethodsUsing GIS techniques, topographic variables were extracted from two DEMs: 1) Shuttle Radar Topography Mission 3 (SRTM3, 90-m resolution) and 2) the Advanced Spaceborne Thermal Emission Reflection Radiometer Global DEM (ASTER, 30-m resolution). We used data on breeding sites from an extensive field survey conducted on an island in western Kenya in 2006. Topographic variables were extracted for 826 breeding sites and for 4520 negative points that were randomly assigned. Logistic regression modelling was applied to characterize topographic features of the malaria vector breeding sites and predict their locations. Model accuracy was evaluated using the area under the receiver operating characteristics curve (AUC).ResultsAll topographic variables derived from both DEMs were significantly correlated with breeding habitats except for the aspect of SRTM. The magnitude and direction of correlation for each variable were similar in the two DEMs. Multivariate models for SRTM and ASTER showed similar levels of fit indicated by Akaike information criterion (3959.3 and 3972.7, respectively), though the former was slightly better than the latter. The accuracy of prediction indicated by AUC was also similar in SRTM (0.758) and ASTER (0.755) in the training site. In the testing site, both SRTM and ASTER models showed higher AUC in the testing sites than in the training site (0.829 and 0.799, respectively). The predictability of habitat types varied. Drains, foot-prints, puddles and swamp habitat types were most predictable.ConclusionsBoth SRTM and ASTER models had similar predictive potentials, which were sufficiently accurate to predict vector habitats. The free availability of these DEMs suggests that topographic predictive models could be widely used by vector control managers in Africa to complement malaria control strategies