Better to Be in Bad Company than to Be Alone? <i>Aedes</i> Vectors Respond Differently to Breeding Site Quality in the Presence of Others

<div><p>This study focuses on two competing species, Aedes aegypti and Aedes albopictus (Diptera: Culicidae), both invasive mosquitoes of the New World. Context-specific competition between immature forms inside containers seems to be an important determinant of the coexistence or displacement of each species in different regions of the world. Here, competition experiments developed at low density (one, two or three larvae) and receiving four different resource food concentration, were designed to test whether Ae. albopictus and Ae. aegypti respond differently to competition, and whether competition can be attributed to a simple division of resources. Three phenotypic traits - larval development, adult survival under starvation and wing length - were used as indicators of performance. Larvae of neither species were limited by resource concentration when they were alone, unlike when they developed with competitors. The presence of conspecifics affected Ae. aegypti and Ae. albopictus, inducing slower development, reduced survival and wing length. The response to resource limitation was different when developing with heterospecifics: Ae. aegypti developing with one heterospecific showed faster development, producing smaller adults with shorter lives, while in the presence of two competitors, development increased and adults lived longer. Aedes albopictus demonstrated a better performance when developing with heterospecifics, with no loss in their development period and improved adult survival. Overall, our results suggest that response to competition can not simply be attributed to the division of resources, and that larvae of both species presented large phenotypic plasticity in their response to the presence or absence of heterospecifics and conspecifics.</p></div

Wing length of <i>Aedes aegypti</i> and <i>Aedes albopictus</i>.

<p>Wing length (mm)–Centered results (Mean±SE) of a) <i>Aedes aegypti</i> and b) <i>Aedes albopictus</i> developed at six different larval density combinations (A: individual alone; B: Larva + 1 conspecific; C: Larva + 2 conspecifics; D: Larva + 1 heterospecific; E: Larva + 1 conspecific +1 heterospecific; F: Larva + 2 heterospecifics) and four food levels (1mg: square; 2mg: circle; 4mg: triangle; 8mg: diamond).</p

Contrasts analyzed between the six different treatment densities combination.

<p>Analysis were performed for <i>Ae</i>. <i>aegypti</i> and <i>Ae</i>. <i>albopictus</i> and the four food concentration offered.</p

Larval development time of <i>Aedes aegypti</i> and <i>Aedes albopictus</i>.

<p>Larval development time (Mean±SE) of a) <i>Aedes aegypti</i> and b) <i>Aedes albopictus</i> developed at six different larval density combinations (A: individual alone; B: Larva + 1 conspecific; C: Larva + 2 conspecific; D: Larva + 1 heterospecific; E: Larva + 1 conspecific +1 heterospecific; F: Larva + 2 heterospecifics) and four food levels (1mg: square; 2mg: circle; 4mg: triangle; 8mg: diamond).</p

Adult survival at starvation of <i>Aedes aegypti</i> and <i>Aedes albopictus</i>.

<p>Adult survival at starvation (days)–Centered results (Mean±SE) of a) <i>Aedes aegypti</i> and b) <i>Aedes albopictus</i> developed at six different larval density combinations (A: individual alone; B: Larva + 1 conspecific; C: Larva + 2 conspecifics; D: Larva + 1 heterospecific; E: Larva + 1 conspecific +1 heterospecific; F: Larva + 2 heterospecifics) and four food levels (1mg: square; 2mg: circle; 4mg: triangle; 8mg: diamond).</p

Surveillance of <i>Aedes aegypti</i>: Comparison of House Index with Four Alternative Traps

<div><p>Introduction</p><p>The mosquito <i>Aedes aegypti</i>, vector of dengue, chikungunya and yellow fever viruses, is an important target of vector control programs in tropical countries. Most mosquito surveillance programs are still based on the traditional household larval surveys, despite the availability of new trapping devices. We report the results of a multicentric entomological survey using four types of traps, besides the larval survey, to compare the entomological indices generated by these different surveillance tools in terms of their sensitivity to detect mosquito density variation.</p><p>Methods</p><p>The study was conducted in five mid-sized cities, representing variations of tropical climate regimens. Surveillance schemes using traps for adults (BG-Sentinel, Adultrap and MosquiTRAP) or eggs (ovitraps) were applied monthly to three 1 km² areas per city. Simultaneously, larval surveys were performed. Trap positivity and density indices in each area were calculated and regressed against meteorological variables to characterize the seasonal pattern of mosquito infestation in all cities, as measured by each of the four traps.</p><p>Results</p><p>The House Index was consistently low in most cities, with median always 0. Traps rarely produced null indices, pointing to their greater sensitivity in detecting the presence of <i>Ae. aegypti</i> in comparison to the larval survey. Trap positivity indices tend to plateau at high mosquito densities. Despite this, both indices, positivity and density, agreed on the seasonality of mosquito abundance in all cities. Mosquito seasonality associated preferentially with temperature than with precipitation even in areas where temperature variation is small.</p><p>Conclusions</p><p>All investigated traps performed better than the House Index in measuring the seasonal variation in mosquito abundance and should be considered as complements or alternatives to larval surveys. Choice between traps should further consider differences of cost and ease-of-use.</p></div

Point estimates (and their 95% confidence intervals) for the parameters of the linear and the saturation models fitted to trap positivity.

<p>Point estimates (and their 95% confidence intervals) for the parameters of the linear and the saturation models fitted to trap positivity.</p

Entomological and meteorological data collected in Santarém (STR), from March 2010 to February 2012.

<p>Refer to <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003475#pntd.0003475.g005" target="_blank">Fig. 5</a> for explanation and Table S5 in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003475#pntd.0003475.s001" target="_blank">S1 Text</a> for the climate regression model used to define the 95% predicted intervals.</p

Entomological and meteorological data collected in Nova Iguaçu (NIG), from July 2011 to June 2012.

<p>Refer to <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003475#pntd.0003475.g005" target="_blank">Fig. 5</a> for explanation and Table S7 in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003475#pntd.0003475.s001" target="_blank">S1 Text</a> for the climate regression model used to define the 95% predicted intervals.</p

Entomological and meteorological data collected in Duque de Caxias (DQC), from November 2009 to October 2010.

<p>Refer to <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003475#pntd.0003475.g005" target="_blank">Fig. 5</a> for explanation and Table S6 in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003475#pntd.0003475.s001" target="_blank">S1 Text</a> for the climate regression model used to define the 95% predicted intervals.</p