DOI: 10.5061/dryad.3tx95x6cz
title: Larval site characteristics of mosquito Aedes aegypti in Rabai, Kenya

description: This dataset is described and analyzed in the paper: "Xia,
 S., Dweck, H. K. M., Lutomiah, J., Sang, R., McBride, C. S., Rose, N. H.,
 Ayala, D., & Powell, J. R. (2021). Larval sites of the
 mosquito Aedes aegypti formosus in forest and domestic
 habitats in Africa and the potential association with oviposition
 evolution. Ecology and Evolution, 00, 1–
 17. https://doi.org/10.1002/ece3.8332" The
 mosquito Ae. aegypti is a major vector of
 several arboviral diseases. In Africa, Ae. aegypti can
 be found in both ancestral forest habitats and human-made domestic
 habitats, such as villages. They also use different types of containers as
 larval sites: while the forest Ae. aegypti use tree
 holes and rock pools, the domestic populations rely mostly on artificial
 contains such as plastic buckets. As an initial attempt to better
 understand Ae. aegypti larval ecology and evolution in
 different habitats, we characterized the
 microenvironment of their larval sites in both habitats and
 compare them. We focus on two localities in Africa: La Lope in Gabon, and
 Rabai in Kenya. The current dataset contains data from Rabai and
 the La Lope data can be found in a different dataset
 (DOI:10.5061/dryad.7m0cfxprg). In this dataset, we characterized
 31 Ae. aegypti larval site from four Rabai
 villages and 37 larval sites from the Rabai forest. Specifically, the
 first ten columns of the dataset provide basic information of each larval
 site, such as sampling location, date, and habitat, etc. The data also
 includes the measures of 16 physical variables of each larva site. These
 variables describe the size of the container, ambient
 environment such as temperature and humidity, and water pH
 and conductivity, etc. Lastly, the dataset has the number
 of Ae. aegypti and other mosquito species found in each
 larval site, as well as measures of microbial density. In addition, we
 also examined the chemical composition of volatiles from a subset of 42
 larval sites. Using GC-MS, we identified chemical compounds in each larval
 site. Using these datasets, we found that forest and village
 larval sites have different microenvironments. The detailed analysis and
 discussion can be found in the paper. We hope this dataset could provide
 useful basic ecological information on Ae.
 aegypti larval habitat in Africa. We encourage future studies to
 explore this dataset and generate more hypotheses on Ae.
 aegypti ecology and evolution. 
description: This dataset was collected during fieldwork in Rabai,
 Kenya between April and May 2017. We collected basic information and
 measured 16 physical characteristics for 68 mosquito larval sites in both
 forest and village habitats. A potential mosquito larval site was defined
 as a water-holding container holding at least one mosquito larva. We also
 collected the headspace volatile samples from 42 larval sites and used
 GC-MS to identify the chemical composition of these samples.
description: In the first dataset ("Larval site data"), the first
 ten columns describe the basic information of each oviposition site
 (n=68). The 11th column indicates whether a site was used in the physical
 analysis. The 12th to the 27th column contains the 16 physical variables
 measured for each site. The 28th column indicates whether the site was
 used in the larval density analysis, and the next four columns contain the
 larval density measures. The 33rd and 34th columns are the information
 about microbial density in the oviposition sites. The 35th column is an
 indicator of which sites have bacterial community composition data. The
 last column indicates whether each site was included in headspace chemical
 analysis. The second dataset ("Chemical
 composition") contains the chemical composition of the headspace
 volatile samples from 42 oviposition sites. The first column contains the
 unique code of each site that matches the first column in "Larval
 site data". The metadata provides more explanation
 on how each variable was recorded or measured in both datasets. Missing
 values are indicated by "NA" in the dataset.