Climate change has the potential to alter the average exposure of human populations to vector-borne diseases like Chagas and leishmaniasis diseases. Both diseases are found in North America. Woodrats (Neotoma species) are known to be Chagas and leishmaniasis diseases’ reservoirs. The main objective of this research is to provide a risk assessment of the present and future (2050) potential distribution of Neotoma micropus in North America. A database with 1,019 geographic locations of Neotoma micropus was compiled in order to correlate this information with 19 climatic variables using MaxEnt software to predict the potential distribution of Neotoma micropus in the study area. MaxEnt produces predictive models based on current climatic data to be projected to future climate conditions. MaxEnt uses present data only and when compared with other software it shows the best results. In total 100 models for this species were developed. Models were evaluated using the Area under the Curve in a ROC plot. The final map was the average map from the 100 models, thus the final AUC was also the average one. A jackknife test was performed in order to assess the importance of climatic variables. Potential distribution of Triatoma gerstaeckeri (Chagas vector) and Lutzomyia diabolica (leishmaniasis vector) were overlapped with the distribution maps of N. micropus in order to assess the impact of the future distributions of these diseases.
Results/Conclusions
The final map predicted that Neotoma micropus suitable habitat ranges from Central Mexico to Northern USA. The variables that have higher contribution for the distribution of Neotoma micropus are: mean temperature of wettest quarter, annual mean temperature, and precipitation of driest month. Potential distribution of vectors of Chagas and leishmaniasis match with potential distribution of the target species reservoir. Further work includes predicting the potential future distribution of Neotoma micropus using two General circulatory models (GCM) from two laboratories: CCCMA (Canadian Center for Climate Modeling and Analysis) and CSIRO (Commonwealth Scientific and Industrial Research Organization).