Freshwater systems are impacted by multiple threats such as pollution, warming, land cover change, and deoxygenation. Monitoring efforts for these systems should utilize bioindicator species, whose prevalence and abundance can inform assessments of habitat quality. In temperate regions, lentic waterbodies commonly fall along a hydroperiod gradient, from ephemeral pools to permanent lakes. Lestes damselflies (Zygoptera: Lestidae) segregate along this gradient, and they are effective bioindicators. As active predators that are aquatic in their juvenile stages but terrestrial as adults, Lestes damselflies connect the aquatic and terrestrial portions of their habitats, and their low dispersal ability links population persistence to local environmental conditions. There are however key obstacles to monitoring their populations, including the spatial patchiness of these damselflies’ distributions, the known detection biases in their presence records, and the lack of prior knowledge on which environmental drivers affect their geographic distributions. As a result, it is difficult to identify probable “hotspots” for a given Lestes species. To address these issues, we applied multi-species distribution models, fit to presence data for ten Lestes species in the state of Michigan. We leveraged three separate frameworks: 1) a stacked species distribution model, 2) hierarchical modeling of species communities (HMSC), which can quantify co-occurrence patterns among species, and 3) a spatiotemporal joint species distribution model within a flexible site-occupancy framework, which can account for imperfect detection by observers. We compared the predictive performance of these three frameworks, used model output to describe the environmental, geographic, and seasonal drivers of each Lestes species’ distribution, and, through a model ensemble approach, identified hotspots in the state of Michigan where these damselflies are more likely to be found.