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Description: Data integration techniques allow sharing of information across multiple data sources. These techniques have the potential to improve inference on habitat use and population trends, while also allowing researchers to better understand the benefits and drawbacks of each data source they use by investigating these data sources within a unified framework. In this seminar, I will demonstrate the potential of data integration techniques using three case studies. In the first case study, we used data on non-native shrub occurrence from the Illinois Critical Trends Assessment Program combined with count data from spotlight surveys to investigate the relationship between non-native shrub occurrence and other habitat factors on mesocarnivore relative abundance in Illinois. In the second case study, we investigated the benefits and pitfalls of integrated state-space models as a tool to estimate population trends in Illinois mesocarnivores and game birds. In the third case study, we used data from the North American Breeding Bird Survey, eBird, and surveys in upland game habitat areas to assess the potential of data integration for improving inference on habitat use of upland game birds in Illinois, while also better understanding the spatial biases in different population monitoring programs. Over all, in this seminar, I seek to demonstrate how data integration can both improve ecological inference and help us better understand the data sources we use for ecological inference.