An index of average percent error is a better estimate of the precision of age determinations than the conventional percent agreement method because it is not independent of the age of a species.Key words: age determination, aging errors

A survey of 500 studies published between 1907 and 1980 that included estimates of fish age indicated that only 65% mentioned age validation or attempted to validate the ageing technique. In less than 3% was the technique validated for all age classes. Among the 35% that did not consider age validation, many did not consider the possibility that ages may be incorrect. Among 75 additional publications published in primary journals between 1965 and 1980 that assessed stock dynamics and used fish ages, only 40% mentioned or attempted age validation, and none successfully validated all age groups used in the analysis. Many investigators continue to neglect the critical study of age validation despite the clear direction of the early work on age determination. We show that estimated ages greater than the maximum validated age must not be considered accurate. Use of inaccurate ages has caused serious errors in the management and understanding of fish populations. Only by mark-recapture studies or use of known-age fish can all age classes in a population be validated. If such studies are not possible, fish should be aged by several methods, and the possibility of errors in age estimates must be considered.

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It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner-recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts.ecosystem forecasting | fisheries ecology | physical-biological interactions | empirical dynamic modeling | nonlinear dynamics O ne of the fundamental challenges of environmental science is to understand and predict the behavior of complex natural ecosystems. This task can be especially difficult when multiple drivers (e.g., species interactions, environmental influences) interact in a nonlinear state-dependent way to produce dynamics that appear to be erratic and nonstationary (1). In the standard parametric approach, which implicitly assumes that the selected model and its equations are essentially correct, the equations (really just mechanistic hypotheses) can lack the flexibility to describe the nonlinear dynamics that occur in nature. Consequently, these parametric models tend to perform poorly as descriptions of reality, with little explanatory or predictive power (2, 3), and limited usefulness for prediction and management. Parametric Models as HypothesesA common problem when applying the parametric approach to nonlinear systems is that of ephemeral fitting. That is, although population models may assume that demographic parameters such as growth rate or carrying capacity are fixed constants, these quantities are often observed to vary in time or in relation to other variables (e.g., resource availability, changing climate regimes) when tested on actual data (4). This principle is illust...

Pink (Oncorhynchus gorbuscha), chum (O. keta), and sockeye salmon (O. nerka) represent approximately 90% of the commercial catch of Pacific salmon taken each year by Canada, Japan, the United States, and Russia. Annual all-nation catches of the three species and of each species, from 1925 to 1989, exhibited long-term parallel trends. National catches, in most cases, exhibited similar but weaker trends. The strong similarity of the pattern of the all-nation pink, chum, and sockeye salmon catches suggests that common events over a vast area affect the production of salmon in the North Pacific Ocean. The climate over the northern North Pacific Ocean is dominated in the winter and spring by the Aleutian Low pressure system. The long-term pattern of the Aleutian Low pressure system corresponded to the trends in salmon catch, to copepod production, and to other climate indices, indicating that climate and the marine environment may play an important role in salmon production.