Strengthening ecologically based rodent management in the Philippines using maximum entropy (MaxEnt) predictions

Abstract

Rattus species pose a significant threat to the Philippines, causing substantial economic losses in agriculture and posing health risks to humans. While Ecologically Based Rodent Management (EBRM) has been developed to mitigate rodent outbreaks, its implementation is challenging, particularly in the face of climate and land use changes. In this study, we aimed to potentially enhance EBRM strategies by utilizing a high-performing modelling approach, MaxEnt, to predict the habitat suitability for Rattus species in the Philippines. This study revealed that forested areas exhibit high suitability for R. tanezumi, R. exulans, and R. everetti, with a notable degree of similarities in their habitat suitability. Furthermore, the model predicted that R. argentiventer, a species with no records in the mainland of Luzon, could potentially find suitable habitats in some areas of these regions, particularly in Central Luzon. Conversely, R. norvegicus was predicted to be highly suitable for areas with high-human population density, such as urban cities. The predictive model deepens our understanding of the interactions between Rattus species and their environments across the Philippines, which is crucial for identifying high-risk areas that require immediate intervention. These results have the potential to enhance the EBRM approach more effectively on a national scale. The EBRM strategy based on the predictive outcomes of the MaxEnt model is not only crucial for the Philippines but also serve as a guiding framework for other regions facing similar challenges with rodent populations.