Abstract
BackgroundMosquito surveys that collect local data on mosquito species’ abundances provide baseline data to help understand potential host-pathogen-mosquito relationships, predict disease transmission, and target mosquito control efforts.MethodsWe conducted an adult mosquito survey from November 2017 to March 2019 on St. Kitts, using Biogents Sentinel 2 traps, set monthly and run for 48-h intervals. We collected mosquitoes from a total of 30 sites distributed across agricultural, mangrove, rainforest, scrub and urban land covers. We investigated spatial variation in mosquito species richness across the island using a hierarchical Bayesian multi-species occupancy model. We developed a mixed effects negative binomial regression model to predict the effects of spatial variation in land cover, and seasonal variation in precipitation on observed counts of the most abundant mosquito species observed.ResultsThere was high variation among sites in mosquito community structure, and variation in site level richness that correlated with scrub forest, agricultural, and urban land covers. The four most abundant species were Aedes taeniorhynchus, Culex quinquefasciatus, Aedes aegpyti and Deinocerites magnus, and their relative abundance varied with season and land cover. Aedes aegypti was the most commonly occurring mosquito on the island, with a 90% probability of occurring at between 24 and 30 (median = 26) sites. Mangroves yielded the most mosquitoes, with Ae. taeniorhynchus, Cx. quinquefasciatus and De. magnus predominating. Psorophora pygmaea and Toxorhynchites guadeloupensis were only captured in scrub habitat. Capture rates in rainforests were low. Our count models also suggested the extent to which monthly average precipitation influenced counts varied according to species.ConclusionsThere is high seasonality in mosquito abundances, and land cover influences the diversity, distribution, and relative abundance of species on St. Kitts. Further, human-adapted mosquito species (e.g. Ae. aegypti and Cx. quinquefasciatus) that are known vectors for many human relevant pathogens (e.g. chikungunya, dengue and Zika viruses in the case of Ae. aegypti; West Nile, Spondweni, Oropouche virus, and equine encephalitic viruses in the case of Cx. quinqefasciatus) are the most wide-spread (across land covers) and the least responsive to seasonal variation in precipitation.
Highlights
Mosquito surveys that collect local data on mosquito species’ abundances provide baseline data to help understand potential host-pathogen-mosquito relationships, predict disease transmission, and target mosquito control efforts
Aedes aegypti (n = 443, mean = 89, SD = 161), Ae. taeniorhynchus (n = 3861, mean = 772, SD = 1830), Cx. quinquefasciatus (n = 1663, mean = 333, SD = 628), and Deinocerites magnus (n = 1577, mean = 315, SD = 797) were species captured in all five land covers
Our post-hoc assessment of our model suggests the effect of precipitation had a strong effect on the relative abundances of Ae. taeniorhynchus, a moderate effect on Ae. aegypti, and smaller effects on Cx. quinquefasciatus and De. magnus
Summary
Mosquito surveys that collect local data on mosquito species’ abundances provide baseline data to help understand potential host-pathogen-mosquito relationships, predict disease transmission, and target mosquito control efforts. The development of population abundance models that leverage count data generated from these surveys, in turn, can be used to predict how mosquito abundances change seasonally and across different land covers. Information of this nature is crucial for describing potential host-pathogen-mosquito relationships in novel transmission foci, accurately predicting disease transmission, and for targeting and assessing the efficacy of mosquito control efforts [8, 9]
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