Recruitment in tuna RFMO stock assessment and management: A review of current approaches and challenges

We review recent approaches and challenges in monitoring and estimating recruitment for the main commercial tuna species managed under the auspices of the five tuna Regional Fisheries Management Organizations (tRFMOs), including: (i) the stock assessment and management context, (ii) fisheries-independent recruitment monitoring successes, failures and future options, (iii) recruitment estimation methods within statistical population models and (iv) recruitment in projections for traditional stock assessment and management strategy evaluation. Despite the diversity in tuna populations and tRFMO scientific processes, there are many common recruitment themes, including: (i) fisheries-independent recruitment monitoring is difficult and rare (the aerial surveys for juvenile southern bluefin tuna, Thunnus maccoyi, and juvenile eastern Atlantic bluefin tuna stocks, T. thynnus, are the only time series used in assessments), (ii) most statistical models estimate lognormal recruitment deviations around a stationary Beverton-Holt relationship using a penalized likelihood approach, (iii) the degree of compensation in the stock-recruitment relationship and the variance is difficult to estimate (steepness is usually fixed at 0.7 <= h <= 1.0, and the CV is most often fixed with sigma(R) = 0.6 for lognormal recruitment deviations), and (iv) estimated recruitment time series often deviate systematically from the mean relationship, but it is unclear the extent to which this reflects reality (e.g. environmental change) or estimation artefacts (e.g. incorrect model assumptions or biased data). There is a trend toward the use of model ensembles to represent recruitment (and other sources of) uncertainty, both in the context of traditional assessments and management strategy evaluation. Recommendations include: i) continued development of fisheries-independent recruitment monitoring methods, including adopting emerging technologies (e.g. genetics-based mark-recapture or abundance monitoring with a network of acoustic FADs), and (ii) the management paradigm should be designed to be robust to future recruitment uncertainties (e.g. recognize that recruitment compensation might be much lower than model-based estimates or assumptions, and be prepared to respond to substantial serially-correlated recruitment deviations, e.g. regime shifts). Following a history of over-exploitation and difficulties in reaching international scientific and management consensus, the CCSBT now provides a leading example of how tuna recruitment issues might be addressed through innovative monitoring, comprehensive modelling of uncertainty, and management with simulation-tested management procedures.