Dataset Information

Using sibship reconstructions to understand the relationship between larval habitat productivity and oviposition behaviour in Kenyan Anopheles arabiensis.

ABSTRACT:

Background

Strategies for combatting residual malaria by targeting vectors outdoors are gaining importance as the limitations of primary indoor interventions are reached. Strategies to target ovipositing females or her offspring are broadly applicable because all mosquitoes require aquatic habitats for immature development irrespective of their biting or resting preferences. Oviposition site selection by gravid females is frequently studied by counting early instar larvae in habitats; an approach which is valid only if the number of larvae correlates with the number of females laying eggs. This hypothesis was tested against the alternative, that a higher abundance of larvae results from improved survival of a similar or fewer number of families.

Methods

In a controlled experiment, 20 outdoor artificial ponds were left uncovered for 4 days to allow oviposition by wild mosquitoes, then covered with netting and first and second instar larvae sampled daily. Natural Anopheles habitats of two different types were also identified, and all visible larvae sampled. All larvae were identified to species, and most samples of the predominant species, Anopheles arabiensis, were genotyped using microsatellites for sibling group reconstructions using two contrasting softwares, BAPS and COLONY.

Results

In the ponds, the number of families reconstructed by each software significantly predicted larval abundance (BAPS R²?=?0.318, p?=?0.01; COLONY R²?=?0.476, p?=?0.001), and suggested that around 50% of females spread larvae across multiple ponds (skip oviposition). From natural habitats, the mean family size again predicted larval abundance using BAPS (R²?=?0.829, p?=?0.017) though not using COLONY (R²?=?0.218, p?=?0.68), but both softwares once more suggested high rates of skip oviposition (in excess of 50%).

Conclusion

This study shows that, whether in closely-located artificial habitats or natural breeding sites, higher early instar larval densities result from more females laying eggs in these sites. These results provide empirical support for use of early instar larval abundance as an index for oviposition site preference. Furthermore, the sharing of habitats by multiple females and the high skip-oviposition rate in An. arabiensis suggest that larviciding by auto-dissemination of insecticide may be successful.

SUBMITTER: Odero JO

PROVIDER: S-EPMC6708163 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Using sibship reconstructions to understand the relationship between larval habitat productivity and oviposition behaviour in Kenyan Anopheles arabiensis.

Odero Joel O JO Fillinger Ulrike U Rippon Emily J EJ Masiga Daniel K DK Weetman David D

Malaria journal 20190823 1

<h4>Background</h4>Strategies for combatting residual malaria by targeting vectors outdoors are gaining importance as the limitations of primary indoor interventions are reached. Strategies to target ovipositing females or her offspring are broadly applicable because all mosquitoes require aquatic habitats for immature development irrespective of their biting or resting preferences. Oviposition site selection by gravid females is frequently studied by counting early instar larvae in habitats; an ...[more]

PMID: 31443645

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Project description:BACKGROUND:In the Solomon Island, the dominant malaria vector, Anopheles farauti, is highly anthropophagic and increasingly exophilic and early biting. While long-lasting insecticide-treated nets remain effective against An. farauti, supplemental vector control strategies will be needed to achieve malaria elimination. Presently, the only World Health Organization recommended supplemental vector control strategy is larval source management (LSM). Effective targeted larval source management requires understanding the associations between abiotic, chemical and biological parameters of larval habitats with the presence or density of vector larvae. METHODS:Potential and actual An. farauti larval habitats were characterized for presence and density of larvae and associated abiotic, chemical and biological parameters. RESULTS:A third of all sampled potential habitats harboured An. farauti larvae with 80% of An. farauti positive habitats being in three habitat classifications (swamps/lagoons, transient pools and man-made holes). Large swamps were the most abundant positive habitats surveyed (43% of all An. farauti positive habitats). Habitats with An. farauti larvae were significantly associated with abiotic (pH, nitrate, ammonia and phosphate concentrations and elevated temperature) and biotic (predators) parameters. CONCLUSION:Large swamps and lagoons are the largest and most abundant An. farauti habitats in the Solomon Islands. Positive habitats were more frequently associated with the presence of predators (vertebrates and invertebrates) and higher water temperatures. Cohabitation with predators is indicative of a complex habitat ecosystem and raises questions about the potential of biological control as an effective control strategy. Increased presence of An. farauti with higher water temperature suggests a potential explanation for the coastal distribution of this species which is not found inland at elevated altitudes where temperatures would be cooler.

Project description:BackgroundMosquito larval source management (LSM) is a valuable additional tool for malaria vector control. Understanding the characteristics of mosquito larval habitats and its ecology in different land use types can give valuable insight for an effective larval control strategy. This study determined the stability and productivity of potential anopheline larval habitats in two different ecological sites: Anyakpor and Dodowa in southern Ghana.MethodsA total of 59 aquatic habitats positive for anopheline larvae were identified, and sampled every two weeks for a period of 30 weeks using a standard dipping method. Larvae were collected using standard dippers and were raised in the insectary for identification. Sibling species of the Anopheles gambiae sensu lato (s.l.) were further identified by polymerase chain reaction. The presence of larval habitats, their stability and larvae positive habitats were compared between the two sites using Mann-Whitney U and the Kruskal-Wallis test. Factors affecting the presence of An. gambiae larvae and physicochemical properties at the sites were determined using multiple logistic regression analysis and Spearman's correlation.ResultsOut of a total of 13,681 mosquito immatures collected, 22.6% (3095) were anophelines and 77.38% (10,586) were culicines. Out of the 3095 anophelines collected, An. gambiae s.l. was predominant (99.48%, n = 3079), followed by Anopheles rufipes (0.45%, n = 14), and Anopheles pharoensis (0.064%, n = 2). Sibling species of the An. gambiae consisted of Anopheles coluzzii (71%), followed by An. gambiae s.s. (23%), and Anopheles melas (6%). Anopheles mean larval density was highest in wells [6.44 (95% CI 5.0-8.31) larvae/dip], lowest in furrows [4.18 (95% CI 2.75-6.36) larvae/dip] and man-made ponds [1.20 (95% CI 0.671-2.131) larvae/dip].The results also revealed habitat stability was highly dependent on rainfall intensity, and Anopheles larval densities were also dependent on elevated levels of pH, conductivity and TDS.ConclusionThe presence of larvae in the habitats was dependent on rainfall intensity and proximity to human settlements. To optimize the vector control measures of malaria interventions in southern Ghana, larval control should be focused on larval habitats that are fed by underground water, as these are more productive habitats.

Dataset Information

Using sibship reconstructions to understand the relationship between larval habitat productivity and oviposition behaviour in Kenyan Anopheles arabiensis.

Background

Methods

Results

Conclusion

Publications

Using sibship reconstructions to understand the relationship between larval habitat productivity and oviposition behaviour in Kenyan Anopheles arabiensis.

Similar Datasets

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