Laboratory oviposition assays
To examine the interaction between larval breeding sites’ conditions and oviposition evolution, we performed laboratory oviposition assays in a common-garden setup. The goal was to examine whether forest and villageAe. aegypti have different oviposition preferences towards a subset of environmental variables that differed between forest and village larval breeding sites.
We established a forest colony and a peridomestic colony from La Lopé using Ae. aegypti collected from larval breeding sites, supplemented with oviposition traps and human landing capture (approved by the National Research Ethics Committee of Gabon under the protocol 0031/2014/SG/CNE). In Rabai, we created six independent village colonies (four domestic colonies and two peridomestic colonies) from the four villages and four forest colonies from the Kaya Bomu forest. We blood-fed the mosquitoes in the field and brought the eggs (i.e., the second generation) back to our lab at Yale University and the McBride lab at Princeton University. The detailed information of the mosquito colonies and protocols for maintaining these colonies are in the Appendix. The Rabai forest colonies correspond to KBO1 and KBO2 in Rose et al. (2020). All laboratory oviposition assays were performed at Yale University. We used the fourth to the sixth generation of mosquitoes in these assays. For simplicity, we refer to the peridomestic and domestic colonies as village colonies.
\begin{equation} OAI=\ \frac{N_{1}-\ N_{2}}{N_{1}+\ N_{2}},\nonumber \\ \end{equation}
where N1 and N2 are the number of eggs deposited in the two cups, respectively. OAIranges from -1 to 1, representing a complete preference for the second choice to a complete preference for the first choice. We performed beta-binomial models in the R package glmmTMB (Brooks et al., 2017) to examine whether colonies differ in their oviposition preference, using the two egg counts in each cage as the dependent variable (Rose et al., 2020). We added the batch/trial IDs as random effects if data testing a specific condition were generated from more than one experimental batch. The statistical significance of colony or habitat effects were determined by comparing the full model with a null model that excludes colony or habitat (Table S9). We extracted mean OAI with a 95% confidence interval from the model using the R packageemmeans (Lenth et al., 2018; Rose et al., 2020).
Using this assay, we compared the oviposition preference of forest versus village colonies from La Lopé and Rabai towards several environmental variables. We first focused on a pair of Rabai forest versus domestic colonies. The conditions tested include: 1) water samples collected from tree holes and artificial containers in Rabai, 2) pH, 3) shading, 4) larval density, 5) a combined effect of pH, conductivity, and shading, and 6) bacterial community composition. We selected these conditions as they showed significant differences between forest and village larval breeding sites in the field. In each assay, the two choices (i.e., two cups) roughly represent the median value of the focal variable measured in forest and village larval breeding sites (described in more detail in the Appendix). For example, in the experiment on water pH, we adjusted the pH in the two cups to the median pH values of all Rabai forest versus village larval breeding sites. Lastly, for the experiment of bacterial community composition, we expanded it to include all Rabai colonies as well as the two La Lopé colonies (Table S2 in the Appendix).
In addition to the above two-choice assays, we tested the oviposition preference of all mosquito colonies to five bacterial densities. This experiment was inspired by the large variation in bacterial density among field larval breeding sites (more than two orders of magnitude) and that previous laboratory experiments with Ae. aegypti found density-dependent ovipositional responses to bacteria (Ponnusamy et al., 2015; Ponnusamy et al., 2010). We used a similar experimental design as the two-choice assays but provided each cage of mosquito females five cups instead of two. The cups contained bacterial cultures at densities ranging from zero to nearly the maximal bacterial density in field larval breeding sites. The bacterial culture was generated from an even mixture of forest and domestic water samples (Table S2 in the Appendix). We counted the numbers of eggs laid in the five cups and fitted a negative-binomial model using the R package lme4 (Bates et al., 2014), with bacterial density, habitat/colony, and their interactions as predictors. If mosquitoes from different colonies or habitat types have different oviposition choices, the interaction term would be significant, which was tested by comparing the full model with a null model excluding the interactive term (Table S9). We added cage ID as a random effect. Lastly, we used the emmeans package to estimate the expected number of eggs in each bacterial density with 95% confidence intervals.