Direct MPA regulations or management plans rarely address the complete set of fishing and activity restrictions in place.
Regulation-based MPA evaluation systems can reliably identify fully and highly protected areas, even with unknown information.
Navigator’s Level of Fishing Protection (LFP) scores can help guide assumptions about unknown information.
Using existing datasets to assign protection levels (following the RBCS or similar) allows for faster global assessments of protection.
Strong human use regulations are an important precondition for marine protected area (MPA) effectiveness. Distinguishing MPAs based on their protection levels has shown advantages, but the availability of regulatory information about allowed activities is a major roadblock towards completing assessments at scale. Here, using a California case study, we explore assigning MPA protection levels following the regulation-based classification system (RBCS) under different scenarios of incomplete regulatory information. In the first group of scenarios (A), only readily available information was used, i.e., information contained in direct MPA implementing regulations and management plans. In the second group (B), information was limited to the activities in ProtectedSeas’ Navigator that matched those in the RBCS. From group A, 99% and 100% correct classification of fully and highly protected areas, respectively, were obtained when treating unknown aquaculture, bottom exploitation, and bottom extraction as ‘prohibited’ and boating, anchoring, and fishing activities as ‘allowed’. High classification accuracy was also obtained for moderately, poorly, and unprotected areas. From group B, 92% and 94% correct classification of fully and highly protected areas were obtained when using the same assumptions for non-fishing activities but using Navigator’s Level of Fishing Protection (LFP) score to guide assumptions about unknown fishing activities. Correct classification rates were poorer with different assumptions. Regulation-based MPA evaluation systems can reliably identify fully and highly protected areas in the face of unknown information, when assumptions about unknown information are guided by contextual indicators such as generally regulated human activities and/or overall level of fishing restriction.