I submitted a new paper (aka tour de force) with title "Determining individual variation in growth and its implication for life history and population processes using the Empirical Bayes method" that is the result of a collaboration between myself, Marc Mangel, Hans Skaug, Steve Munch and Alain Crivelli. Four nations (Italy, US, Norway and France), multiple projects, one paper.
Here is the 200-word abstract:
The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation.
We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth with a random-effects model. As a case study, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually‑tagged fish have been sampled for more than 15 years. We introduce cohort and density during the first year of life as potential predictors of the von Bertalanffy growth function’s parameters k and in addition to the individual random effects.
Our results showed that size ranks were largely maintained throughout lifetime in both populations. The best models according to the Akaike Information Criterion showed different growth patterns for year of birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. Model predictions of individual growth trajectories were largely more accurate than predictions based on mean size-at-age of fish. We consider both the life history origins of these patterns and their implications.
You can find data, code and a preprint on figshare. To run the code you need to install ADMB (I used version 11) and R. I think the total line of codes are between 5 and 10 thousand. It has been a long work (aka tour de force) and not-soon-to-be repeated.