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.
Molecular tip dating of phylogenetic trees is a growing discipline that uses DNA sequences sampled at different points in time to coestimate the timing of evolutionary events with rates of molecular evolution. In this context, beast, a program for Bayesian analysis of molecular sequences, is the most widely used phylogenetic tool. Here, we introduce tipdatingbeast, an r package built to assist the implementation of various phylogenetic tip-dating tests using beast. tipdatingbeast currently contains two main functions. The first one allows preparing date-randomization analyses, which assess the temporal signal of a data set. The second function allows performing leave-one-out analyses, which test for the consistency between independent calibration sequences and allow pinpointing those leading to potential bias. We apply those functions to an empirical data set and supply practical guidance for results interpretation.
The population densities of many organisms have changed dramatically in recent history. Increases in the population density of medically relevant organisms are of particular importance to public health as they are often correlated with the emergence of infectious diseases in human populations. Our aim is to delineate increases in density of a common disease vector in North America, the blacklegged tick, and to identify the environmental factors correlated with these population dynamics. Empirical data that capture the growth of a population are often necessary to identify environmental factors associated with these dynamics. We analyzed temporally- and spatially-structured field collected data in a geographical information systems framework to describe the population growth of blacklegged ticks (Ixodes scapularis) and to identify environmental and climatic factors correlated with these dynamics. The density of the ticks increased throughout the study’s temporal and spatial ranges. Tick density increases were positively correlated with mild temperatures, low precipitation, low forest cover, and high urbanization. Importantly, models that accounted for these environmental factors accurately forecast future tick densities across the region. Tick density increased annually along the south-to-north gradient. These trends parallel the increases in human incidences of diseases commonly vectored by I. scapularis. For example, I. scapularis densities are correlated with human Lyme disease incidence, albeit in a non-linear manner that disappears at low tick densities, potentially indicating that a threshold tick density is needed to support epidemiologically-relevant levels of the Lyme disease bacterium. Our results demonstrate a connection between the biogeography of this species and public health.
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