Abstract

Temporal dynamics of ecological processes are complex, and their influence on species-habitat relationships and species distribution operates on various spatial and temporal scales. Researchers often use spatio-temporal point process models to model species habitat relationships and predict species distribution across different spatial and temporal scales; however, their robustness to changing temporal scales is rarely studied. Our research investigates how changes in the temporal support impact the robustness of these models to ensure accurate insights into species distribution across time. We utilize data fusion, combining distance sampling and capture-recapture data through a spatio-temporal point process model overcoming individual data source limitations, and then assess the robustness of spatio-temporal point process models to changing temporal scales enhancing our ability to study species distribution in complex spatio-temporal contexts.