Strategies for improving the precision of fishing and natural mortality estimates from multiyear tagging models: a case study

Abstract

Fisheries scientists and managers want precise estimates of fishing and natural mortality for assessments and management decisions. Because tagging can be an expensive option, maximizing potential benefits requires careful consideration of experimental design. We evaluated four options for improving the precision of estimates by conducting Monte Carlo simulations of a fishery patterned after that for the rock lobsters in north-western Tasmania, Australia. Improving tag-reporting rate and increasing the duration of the tagging study provided greater improvements in precision than increasing either the number of lobsters tagged per tagging event or the number of tagging events each year. A design based on twice-a-year tagging for three years to determine tagreporting rate followed by an additional two or more years of once-a-year tagging provided the most precise estimates of natural mortality of all the designs considered. This design was also cost effective relative to the other options, but tag-reporting rate must be constant over the period of the study. If constancy cannot be assumed, then years of multiple tagging events may have to be interspersed among the years with single tagging events. Further improvements in mortality estimates from this multiyear tagging model could be achieved with improved tagreporting rate.