application to Pacific, Atlantic and Indian Ocean tuna stocks

Peak-to-peak (PP) and general additive modeling (GAM) approaches were used to estimate fishing capacity and related quantities based on stock assessment information. Sensitivity tests revealed greater estimates of capacity output when the stock assessment data were most disaggregated. Further tests revealed that the estimates of overcapacity were lower when low variability in effort deviations was permitted in the stock assessment. The PP and GAM methods were applied to seven stocks of bigeye, yellowfin and skipjack tuna of the Pacific, Indian and Atlantic Oceans. The estimated trends in overcapacity with both methods were consistent across most of the stocks, showing increasing trends at the beginning of the time series and reaching maximum values during the late 1990s, followed by a decreasing trend after that. For most of the stocks analyzed, overcapacity was positive during part of the time series