Identifying the effects of climatic (e.g. temperature) or environmental drivers (e.g. land cover variability, invasive species) on species assemblages and abundances has historically been a topic of interest. However, isolating such processes from snapshot data is challenging since they might leave similar footprints. Monitoring surveys might help in teasing them apart by informing the population variability of taxa that may serve as indicator for the health of ecosystems. Ants (Hymenoptera: Formicidae) are an exemplar system for monitoring ecosystem health and function because of their dominance in biomass and diversity in form and function. In this study, we aim to: a) understand how factors representing different climatic (i.e. temperature and precipitation) and environmental (i.e. land cover, alien species) variables shape the abundance of ant communities, and b) identify non-random species associations (co-occurrence, or lack thereof) that are not explained by predictor variables and determine if such associations could represent actual species interactions. Using a fine-scale (biweekly) time-series (2 years) of ant abundance data from 24 sampling locations across gradients of development on the subtropical island of Okinawa, Japan, we seek to determine the main drivers of ant community dynamics using a hierarchical joint species distribution modeling approach.