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Modeling Potential Habitat for Amblyomma Tick Species in California

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Modeling Potential Habitat for Amblyomma Tick Species in California

Emily L Pascoe et al. Insects.

Abstract

The Amblyomma genus of ticks comprises species that are aggressive human biters and vectors of pathogens. Numerous species in the genus are undergoing rapid range expansion. Amblyomma ticks have occasionally been introduced into California, but as yet, no established populations have been reported in the state. Because California has high ecological diversity and is a transport hub for potentially parasitized humans and animals, the risk of future Amblyomma establishment may be high. We used ecological niche modeling to predict areas in California suitable for four tick species that pose high risk to humans: Amblyomma americanum, Amblyomma maculatum, Amblyomma cajennense and Amblyomma mixtum. We collected presence data in the Americas for each species from the published literature and online databases. Twenty-three climatic and ecological variables were used in a MaxEnt algorithm to predict the distribution of each species. The minimum temperature of the coldest month was an important predictor for all four species due to high mortality of Amblyomma at low temperatures. Areas in California appear to be ecologically suitable for A. americanum, A. maculatum, and A. cajennense, but not A. mixtum. These findings could inform targeted surveillance prior to an invasion event, to allow mitigation actions to be quickly implemented.

Keywords: Amblyomma; MaxEnt; invasive species; species distribution modeling; ticks.

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure A1
Figure A1
Heatmap of habitat suitability in California for four exotic Amblyomma tick species, predicted using MaxEnt species distribution modeling: (a) A. americanum; (b) A. maculatum; (c) A. cajennense; and (d) A. mixtum.
Figure 1
Figure 1
The current USA distributions of Amblyomma americanum (the lone star tick) and A. maculatum (the Gulf Coast tick) based on the generation of a convex polygon around geolocations for each species from the scientific literature and online databases collected for MaxEnt modeling (see Supplementary Materials for full list of geolocations).
Figure 2
Figure 2
Geolocations used in MaxEnt modeling to predict suitable habitat in California for four Amblyomma tick species: (a) A. americanum, (b) A. maculatum, (c) A. cajennense, and (d) A. mixtum. Presence geolocations (yellow circles) were obtained from the published literature and open access databases, and background geolocations (blue squares) were simulated according to assumed presence sampling bias.
Figure 3
Figure 3
Estimated smoothed trends (using locally estimated scatterplot smoothing (LOESS) with span = 1) and 95% confidence intervals between environmental predictor variables and predicted habitat suitability in MaxEnt models for four exotic Amblyomma species: (a) A. americanum; (b) A. maculatum; (c) A. cajennense; and (d) A. mixtum. Trends were derived from the ratio of probability density of each predictor at presence to background geolocations, considering data from 10 iterations used for model training and testing.
Figure 4
Figure 4
Habitat in California predicted (using MaxEnt species distribution modeling) to be environmentally suitable for four exotic Amblyomma tick species: (a) A. americanum; (b) A. maculatum; (c) A. cajennense; and (d) A. mixtum. Areas shaded in green represent potentially suitable habitat at a probability threshold at which all tick training presence geolocations were correctly classified as suitable by the model and which maximized correct classification of background geolocations. Hot arid desert was masked from suitability for A. maculatum and A. cajennense.

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