RUMINATIONS ON THE DEVELOPMENT AND FUTURE OF POPULATION DYNAMICS MODELS IN FISHERIES
Authors: QUINN TERRANCE J. 
Published: August 2010

ABSTRACT.I trace the development of fisheries models (i.e., fish population dynamics models of species subject to fisheries) to the 21st century. The first real efforts occurred in the period 1900 1920 with the work of Baranov (the “Grandfather” of fisheries population dynamics) and the formation of the International Council for the Exploration of the Sea (ICES). The establishment of the science occurred between 1920 1960 with multi‐species modeling, age‐ and size‐structure dynamics, and production models. Fundamental work during this time was done by Ricker (the “Father” of fisheries population dynamics), Beverton and Holt (the “Prophets” of fisheries population dynamics), Chapman, Dickie, DeLury, Graham, Gulland, Leslie, Lotka and Volterra, Russell, Schaefer, and Thompson. During this time, most of the workwas deterministic and mathematical. Between 1960 and 1980, statistical methodology evolved greatly but was separate from mathematical advances for the most part. The development of statistical principles for the estimation of animal abundance was further enhanced by Arnason, Buckland, Burnham and Anderson and White, Cormack, Eberhardt, Jolly, Manly, Pollock, Ricker, Robson, and Seber, among others. Fisheries models evolved in a deterministic setting, with advances in age‐structured models (Gulland, Pope, Doubleday), surplus production models (Pella, Tomlin‐son, Schnute, Fletcher, Hilborn), growth models, bioeconomic models (C. Clark) and management control models (Hilborn, Walters). The period 1980 2000 was the Golden Age. The integration between mathematics and statistics occurred when likelihood and least squares techniques were formally combined with mathematical models of population change. The number of fisheries modelers grew exponentially during this time, resulting in a concomitant increase in publications. A major advance in the 1990s has been the development of Bayesian and time series methods, which have allowed explicit specification of uncertainty. Currently, theory allows realistic modeling of age‐ and size‐structured populations, migratory populations and harvesting strategies. These models routinely incorporate measurement error, process error (stochasticity) and time variation. But data needs often overwhelm the performance of models, and greater demands are being placed on models to answer complex questions. There has been poor communication between fisheries and ecological modelers, between fisheries researchers and statisticians, and among fisheries researchers in different geographic locales. Future models will need to deal better with habitat and spatial concerns, genetics, multispecies interactions, environmental factors, effects of harvesting on the ecosystem, model misspecification and so‐cioeconomic concerns. Meta‐analysis, retrospective analysis and operating models are some modern approaches for dealing with uncertainty and providing for sustainable fisheries. However, I fear that current attacks on single‐species models and management may result in rejection of these advances and an attempt to substitute a less scientific approach.