We provide an analysis of the invasion and spread of the container inhabiting mosquitoes Aedes aegypti and Aedes albopictus in the Bermuda Islands. Considered eradicated in the mid-1960s, A. aegypti was redetected in 1997, and A. albopictus was first detected in 2000. Based on weekly ovitrap data collected during the early stages of the invasion, we mapped the spread of Aedes throughout the islands. We analyzed the effects of buildings and roads on mosquito density and found a significant association between density and distance to roads, but not to buildings. We discuss the potential role of human transport in the rapid spread in the islands. The temporal correlation in ovitrap collection values decreased progressively, suggesting that habitat degradation due to control efforts were responsible for local shifts in mosquito densities. We report a sharp decrease in A. aegypti presence and abundance after the arrival of A. albopictus in the year 2000. Possible mechanisms for this rapid decline at relatively low density of the second invader are discussed in the context of classical competition theory and earlier experimental results from Florida, as well as alternative explanations. We suggest that support for the competition hypothesis to account for the decline of A. aegypti is ambiguous and likely to be an incomplete explanation.
The present work evaluates the use of species distribution model (SDM) algorithms to classify high density of small container Aedes mosquitoes at a fine scale, in the Bermuda islands. Weekly ovitrap data collected by the Health Department of Bermuda (UK) for the years 2006 and 2007 were used for the models. The models evaluated included the following algorithms: Bioclim, Domain, GARP, logistic regression, and MaxEnt. Models were evaluated according to performance and robustness. The area Receiver Operating Characteristic (ROC) curve was used to evaluate each model’s performance, and robustness was assessed considering the spatial correlation between classification risks for the two datasets. Relative to the other algorithms, logistic regression was the best model for classifying high risk areas, and the maximum entropy approach (MaxEnt) presented the second best performance. We report the importance of covariables for these two models, and discuss the utility of SDMs for vector control efforts and the potential for the development of scripts that automate the task of creating risk assessment maps.
Bermuda is a densely populated coral 'atoll' located on a seamount in the mid-Atlantic (Sargasso Sea). There is no national sewerage system and the ∼20 × 10(6) L of sewage generated daily is disposed of via marine outfalls, cess pits/septic tanks underneath houses and through waste disposal (injection) wells. Gastrointestinal (GI) enterococci concentrations were measured in surface seawater samples collected monthly at multiple locations across the island over a 5-year period. According to the EU Bathing Water Directive microbial classification categories, 18 of the sites were in the 'excellent' category, four sites in the 'good', five sites were in the 'sufficient' and three sites in the 'poor' categories. One of the sites in the 'poor' category is beside a popular swimming beach. Between 20-30% of 58 sub tidal sediment samples collected from creeks, coves, bays, harbours and marinas in the Great Sound complex on the western side of Bermuda tested positive for the presence of the human specific bacterial biomarker Bacteroides (using culture-independent PCR-based methods) and for the faecal biomarker coprostanol (5β-cholestan-3-β-ol, which ranged in concentration from <0.05-0.77 mg kg( - 1). There was a significant statistical correlation between these two independent techniques for faecal contamination identification. Overall the microbial water quality and sedimentary biomarker surveys suggest sewage contamination in Bermuda was quite low compared with other published studies; nevertheless, several sewage contamination hotpots exist, and these could be attributed to discharge of raw sewage from house boats, from nearby sewage outfalls and leakage from septic tanks/cess pits.
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