Information about human activities along the coast can help us understand human impacts on natural resources and the benefits people derive from marine protected areas (MPAs). In this project we examined human activities along the California coast from 2012 to 2020 using data from the MPA Watch community science network, gathered by more than 1,900 volunteer participants, and a handful of program staff. MPA Watch is gathering useful data at a statewide scale, and has successfully grown its network of volunteer monitoring programs over the last decade to include 12 local programs, 104 monitoring sites, and hundreds of volunteer surveyors each year. Among the observations recorded by MPA Watch surveyors, non-consumptive recreational activities vastly outnumber consumptive activities like fishing, both inside and outside of MPAs. This highlights the value of MPA Watch data for understanding human coastal use, underscores the importance of recreational activities in California’s coastal economy, and reinforces the need to monitor and understand non-consumptive uses in and around MPAs. Our analysis confirms that MPA Watch data can detect broad, statistically robust patterns in human activities along the coast, including among recreational activities that relate to Goal 3 of the Marine Life Protection Act, but have not been the focus of other socioeconomic monitoring projects. MPA Watch data can also be used to detect statistically significant differences between activities inside and outside of MPAs: we used occupancy modeling to investigate the likelihood of occurrence of seven different categories of human activities. From 2012 to 2020 at the statewide level, onshore fishing was less likely inside of MPAs, and tidepooling and recreational boating were more likely inside of MPAs (we found no difference in probability of occurrence for offshore fishing, domestic animals, or onshore or offshore recreation). We conclude with some recommendations for improving MPA Watch data collection protocols, for expanding the use of the data by managers and law enforcement, and for future in-depth analyses that incorporate more of the richness of the dataset