Results of a classification tree aimed to identify the most likely fishery management attributes related to the sustainability of fisheries. In a classification/regression tree, the factor that maximizes differences in fisheries sustainability is placed at the root of the tree, and the EEZs in each of its quarters are separated into different branches. This method repeatedly tests for significant differences among the EEZs in each branch in the remaining attributes and stops when no significant difference exists in any attribute within the EEZs of any branch (see Materials and Methods). The results shown here include the linking between the probability of fisheries sustainability (P
sust) and each of the management attributes analyzed: scientific robustness, policymaking transparency, implementation capability, fishing capacity, subsidies, access to foreign fishing, and country wealth.