Abstract
(308 of 350 word max) 1. Calls for using marine protected areas (MPAs) to achieve goals for nature and people are increasing globally. While the conservation and fisheries impacts of MPAs have been comparatively well studied, impacts on other dimensions of human use have received less attention. Understanding how humans engage with MPAs and identifying traits of MPAs that promote engagement is critical to designing MPA networks that achieve multiple goals effectively, equitably, and with minimal environmental impact. 2. In this paper, we characterize human engagement in California's MPA network, the largest scientifically-based network of MPAs in the world (124 MPAs spanning 16% of state waters and 1,700 km of coastline), and identify traits associated with higher human engagement. We assemble and compare diverse indicators of human engagement that capture recreational, educational, and scientific activities across California's MPAs. 3. We find that human engagement is correlated with nearby population density and that site "charisma" can expand human engagement beyond what would be predicted based on population density alone. Charismatic MPAs tend to be located near tourist destinations, have long sandy beaches, and be adjacent to state parks and associated amenities. In contrast, underutilized MPAs were often more remote and lacked both sandy beaches and parking lot access. 4. Synthesis and applications: These results suggest that achieving MPA goals associated with human engagement can be promoted by developing land-based amenities that increase access to coastal MPAs or by locating new MPAs near existing amenities during the design phase. Alternatively, human engagement can be limited by locating MPAs in areas far from population centers, coastal amenities, or sandy beaches. Furthermore, managers may want to prioritize monitoring, enforcement, education, and outreach programs in MPAs with traits that predict high human engagement. Understanding the extent to which human engagement impacts the conservation performance of MPAs is a critical next step to designing MPAs that minimize tradeoffs among potentially competing objectives.