Exploring temperature effects on tick population dynamics: What are agent-based models saying?

Agent-based models can be applied to infer the effects of climate change on complex ecological systems such as addressing the behaviour of the vector-host system under temperature change and assess its effects on vector activity and density. Ticks are important vectors of pathogens that cause the spread of many tick-borne diseases. The tick population dynamics depend on several biotic and abiotic factors, such as temperature and host density. Such complexity of dependence and non-linear interactions makes it challenging to predict the dynamics and density of ticks under a changing climate. The objective of this study is to evaluate the reconstructed temperature signals using an agent-based model, where we only consider temperature to be the limiting abiotic factor influencing the development of ticks to infer patterns of tick population dynamics. We parametrized the model using the blacklegged tick Ixodes scapularis data and we simulated tick population dynamics for ten years in five scenarios in which we modified the input temperature signals. We found that tick responses to changing spring-autumn and constant trends vary considerably. Higher interseason duration leads to more stable but lower overall populations, whereas, conversely, very low interseason duration results in substantial population growth. Extending the duration of the warm season led to a population explosion, while an increase in the cold season resulted in a low population abundance and decreasing trends. These results highlight the importance of season duration variability and potential non-linearity in the tick population’s response to environmental change.