Comment; Great approach to predictive geography/cartography & epidemiology using the factors the FL team used to predict tick density!
,Claudia Ganser 1 andGregory E. Glass 21Department of Geography, University of Florida, Gainesville, FL 32611, USA2Department of Geography, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611, USA*Author to whom correspondence should be addressed.Insects2019, 10(7), 190; https://doi.org/10.3390/insects10070190Received: 15 April 2019 / Revised: 18 May 2019 / Accepted: 20 June 2019 / Published: 28 June 2019(This article belongs to the Special Issue Tick Surveillance and Tick-borne Diseases) Full-Text | PDF [6245 KB, uploaded 28 June 2019] | Figures
Abstract
The lone star (Amblyomma americanum), black-legged (Ixodes scapularis) and American dog ticks (Dermacentor variabilis) are species of great public health importance as they are competent vectors of several notable pathogens. While the regional distributions of these species are well characterized, more localized distribution estimates are sparse. We used records of field collected ticks and an ensemble modeling approach to predict habitat suitability for each of these species in Florida. Environmental variables capturing climatic extremes were common contributors to habitat suitability. Most frequently, annual precipitation (Bio12), mean temperature of the driest quarter (Bio9), minimum temperature of the coldest month (Bio6), and mean Normalized Difference Vegetation Index (NDVI) were included in the final models for each species. Agreement between the modeling algorithms used in this study was high and indicated the distribution of suitable habitat for all three species was reduced at lower latitudes. These findings are important for raising awareness of the potential for tick-borne pathogens in Florida.
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