Cellular automata (CA) are dynamic models that are discrete in time, space, and state. They are useful for spatial-temporal modeling and have been widely applied to different ecological problems. However, direct applications dealing with invasive species spread are still scarce. In this study we developed a CA model to simulate the spatial-temporal dynamics of the potato tuber moth Tecia solanivora (Lepidoptera: Gelechiidae). This species has been invading the Northern Andes for the last 15 years and constitutes today an important pest of potatoes, the economically most important crop in the Andean region. A deterministic form of the model based on the physiological response of moths to temperatures and precipitations was used to simulate moth spatial dynamics in a small valley invaded by the pest since 2006. In order to understand the effects of anthropogenic activities on moth propagation we tested for the importance of three stochastic variables that have an impact on moth population dynamics: 1) the random presence of traditional potato stores that modify local microclimatic conditions, 2) agricultural practices by farmers, and 3) passive transportation in human vehicles (long-distance dispersal, LDD).

Results/Conclusions

Our results showed that both traditional potato stores and long-distance dispersal had the most significant effects on moth propagation dynamics in the front zones of invasion. The inclusion of LDD in the model was necessary to understand the observed rapid propagation of the pest in the valley during the last years. Potato storage structures were found to buffer extreme air temperatures and provided ideal microclimatic conditions for pest population increase. Therefore, allowing pest establishment in otherwise uncolonized cold parts of the valley. When expanded to the country level, the predictions of our model were still accurate when compared to abundance field data, obtained through monitoring at 80 sites throughout Ecuador. This confirms the significant effect of temperatures, but not of precipitations, on pest densities. The results obtained with this model will later serve as tools for predicting the risk of invasion by this pest in other areas. In addition, they will be divulged to Ecuadorian institutions involved in agricultural and food security programs in order to improve agro-entomological risk management.