Co-occurrence of environmental stressors is ubiquitous in ecosystems, but cumulative effects are difficult to predict for effective indicator development. Individual stressors can amplify (synergies) or lessen (antagonisms) each other's impacts or have fully independent effects (additive). Here we use the Laurentian Great Lakes, where a multitude of stressors have been studied for decades, as a case study for considering insights from both a systematic literature review and an expert elicitation (or structured expert judgment) to identify stressor interactions. In our literature search for pairs of stressors and interaction-related keywords, relatively few studies (9%, or 6/65) supported additive interactions with independent stressor effects. Instead, both antagonisms (42%, or 27/65) and synergies (49%, or 32/65) were common. We found substantial evidence for interactions of invasive dreissenid mussels with nutrient loading and between pairs of invasive species (predominantly dreissenids × round goby), yet both sets of records included mixtures of synergies and antagonisms. Complete quantification of individual and joint effects of stressors was rare, but effect sizes for dreissenid mussels × nutrient loading supported an antagonism. Our expert elicitation included discussion in focus groups and a follow-up survey. This process highlighted the potential for synergies of nutrient loading with dreissenid mussels and climate change as seen from the literature review. The elicitation also identified additional potential interactions less explored in the literature, particularly synergies of nutrient loading with hypoxia and wetland loss. To stimulate future research, we built a conceptual model describing interactions among dreissenid mussels, climate change, and nutrient loading. Our case study illustrates the value of considering results from both elicitations and systematic reviews to overcome data limitations. The simultaneous occurrence of synergies and antagonisms in a single ecosystem underscores the challenge of predicting the cumulative effects of stressors to guide indicator development and other management and restoration decisions.