Predicting the Potential Global Distribution of Amblyomma americanum (Acari: Ixodidae) under Near Current and Future Climatic Conditions, Using the Maximum Entropy Model

Abstract

Amblyomma americanum (the lone star tick) is a pathogen vector, mainly from eastern North America, that bites humans. With global integration and climate change, some ticks that are currently confined to a certain place may begin to spread out; some reports have shown that they are undergoing rapid range expansion. The difference in the potential geographic distribution of A. americanum under current and future climatic conditions is dependent on environment variables such as temperature and precipitation, which can affect their survival. In this study, we used a maximum entropy (MaxEnt) model to predict the potential geographic distribution of A. americanum. The MaxEnt model was calibrated at the native range of A. americanum using occurrence data and the current climatic conditions. Seven WorldClim climatic variables were selected by the jackknife method and tested in MaxEnt using different combinations of model feature class functions and regularization multiplier values. The best model was chosen based on the omission rate and the lowest Akaike information criterion. The resulting model was then projected onto the global scale using the current and future climate conditions modeled under four greenhouse gas emission scenarios.

Keywords: Amblyomma americanum; MaxEnt; climate change; species distribution modeling; ticks.

Figure 1

The output of the Maxent model’s for the training omission rate and predicted area as a function of the cumulative threshold.

Figure 2

Current occurrence and global distribution of A. americanum.

Figure 3

Predicted area suitability under near current climatic conditions. The predicted potential geographic distribution of A. americanum is not only in the current occurrence area.

Figure 4

Jackknife analysis results showing the environmental variables and regularized training gain. Prec5 significantly contributed to the suitability of the areas of A. americanum and Bio4 has the most information that other environmental variables do not have.

Figure 5

Response curves of environmental variables to the distribution probability of A. americanum: (a) Precipitation in May, (b) precipitation of the driest month, (c) temperature seasonality (standard deviation × 100), (d) monthly average maximum temperature in October, (e) mean diurnal range (mean of monthly (max temp–min temp)), (f) precipitation in September and (g) elevation. Curves shown are averages over 20 replicate runs; blue margins show the ±SD calculated over 20 replicates.

Figure 6

The potential distribution of suitable areas for A. americanum around the world under the climatic conditions of shared socio-economic pathway 1–2.6 (sustainability and radiative forcing of 2.6 W/m² to 2100) during different periods of the 21st century: (a) 2021–2040, (b) 2041–2060, (c) 2061–2080 and (d) 2081–2100.

Figure 7

The potential distribution of suitable areas for A. americanum around the world under the climatic conditions of shared socio-economic pathway 2–4.5 (middle of the road and radiative forcing of 4.5 W/m² to 2100) during different periods of the 21st century: (a) 2021–2040, (b) 2041–2060, (c) 2061–2080, (d) 2081–2100.

Figure 8

The potential distribution of suitable areas for A. americanum around the world under the climatic conditions of shared socio-economic pathway 3–7.0 (regional rivalry and radiative forcing of 7.0 W/m² to 2100) during different periods of the 21st century: (a) 2021–2040, (b) 2041–2060, (c) 2061–2080, (d) 2081–2100.

Figure 9

The potential distribution of suitable areas for A. americanum around the world under the climatic conditions of shared socio-economic pathway 5–8.5 (fossil-fueled development and radiative forcing of 8.5 W/m² to 2100) during different periods of the 21st century: (a) 2021–2040, (b) 2041–2060, (c) 2061–2080, (d) 2081–2100.