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Aquatic invasive species (AIS) threaten lake ecosystems and economies. In Minnesota, over 800 waterbodies contain one or more known AIS. However, this number is likely an underestimate due to the lack of a widespread, standardized AIS monitoring program. This is partly due to traditional monitoring for AIS being time and resource intensive. Environmental DNA (eDNA) has the potential to alleviate these issues, but many questions persist about how eDNA AIS detection probability can be optimized across multiple species with different life histories. To quantify time-varying probability of detection of AIS using eDNA sampling, we sampled 21 lakes at 10 sampling locations 5 times over the open water season. Each lake had known populations of invasive common carp, rusty crayfish, spiny water flea, and zebra mussels. We used quantitative Polymerase Chain Reaction with species-specific assays to determine presence of each species in water samples. Using occupancy models, we quantified the effects of lake characteristics and sampling season on eDNA detection probability. Our results suggest that optimal eDNA sampling varies seasonally and is related to the species' life history. Our results will provide guidance to those interested in using eDNA as a monitoring tool. [ABSTRACT FROM AUTHOR]