Climate, human population density, and land cover link the distributions
of two globally important dengue vectors from local to continental
scales
Abstract
The distributions of mosquito vectors are expected to shift with rising
temperatures due to climate change. But other global change patterns,
like land cover change and human population growth, are simultaneously
occurring. How will these changes interact to shift the future
distributions of these vectors? Here, we analyzed how climate, land
cover, and human population density regulate and predict habitat for two
mosquito species, Aedes aegypti and Ae. albopictus, the primary vectors
of dengue, Zika and chikungunya. We asked the following questions: How
do environmental response curves derived from vector occurrence data
compare to lab-derived responses? Based on these environmental response
curves, which environmental drivers best predict the spatial
distribution of each vector? Are environmental responses derived from
large-scale (continental) occurrence data consistent at fine spatial
scales? To answer these questions, we analyzed 6,317 Ae. aegypti
occurrence records, 3,629 Ae. albopictus records, 10 satellite-derived
environmental covariates, and two independent field surveys cover 134
sites. We found close agreement in the range of lab and environmental
temperature responses, though the mean of observed temperatures was
higher in the environment (31.0 °C for Ae. aegypti, 29.1 °C for Ae.
albopictus) than lab predictions of the thermal optimum for transmission
(29.1 °C for Ae. aegypti, 26.4 °C for Ae. albopictus). Using
presence-only species distribution modeling approaches, we found that
human population density was the best predictor for each vector’s
spatial distribution (explaining 68.4% of model performance for Ae.
aegypti, 48.7% for Ae. albopictus). These patterns were consistent in
the field for presence/absence Ae. aegypti data (0.71 AUC, 0.80 recall),
but failed to predict Ae. albopictus distributions in the sites we
surveyed (0.53 AUC, 0.20 recall). In this session, we will explore these
results and discuss the potential to predict and monitor Aedes habitat
using satellite data.